argumentative essay about social media memes

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Lay summary, internet memes, social media, credibility, and persuasion, credibility and online health information, message tone, limitations, contributions and recommendations, appendix a: sample of anti- and pro-mask/memes, appendix b: anti- and pro-vaccine/memes, appendix c: sample of instrument, memes, memes, everywhere, nor any meme to trust: examining the credibility and persuasiveness of covid-19-related memes.

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Ben Wasike, Memes, Memes, Everywhere, nor Any Meme to Trust: Examining the Credibility and Persuasiveness of COVID-19-Related Memes, Journal of Computer-Mediated Communication , Volume 27, Issue 2, March 2022, zmab024, https://doi.org/10.1093/jcmc/zmab024

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This study used an experimental design to examine the credibility and persuasiveness of COVID-19-related Internet memes. The study used a random sample of U.S. social media users (N = 1,200) with source credibility as the theoretical framework. Results indicate that memes with expert source attribution are more credible than those with nonexpert source attribution. The same applies to the persuasiveness of the memes. Memes with an objective message tone are also more credible and persuasive than those with a subjective message tone. Additionally, there is a positive correlation between the credibility of a meme and its persuasiveness. Age correlates inversely with persuasion and pro-mask/vaccine memes are more credible and persuasive than anti-mask/vaccines memes. These results have implications regarding COVID-19 messaging as well as on meme-based communication.

This study examined the credibility and persuasiveness of COVID-19-related Internet memes. This approach is important given the widespread use of social media during the pandemic and the rise of meme-based communication on social media. The study found that memes from an expert source are more credible and persuasive than those from a nonexpert source. The same applied to memes with an objective message over those with a subjective message. The credibility of a meme also improved its persuasiveness, meaning that users were more likely to like it, comment on it, and share it with others. As expected, younger people were more likely to like, share, and comments on memes. Overall, pro-mask/vaccine memes were more credible and persuasive than anti-mask/vaccines memes. These results suggest that public health campaigns may benefit by incorporating memes in their communications.

When you plant a fertile meme in my mind you literally parasitize my brain, turning it into a vehicle for the meme’s propagation in just the way that a virus may parasitize the genetic mechanism of a host cell ( Richard Dawkins, 1976 , p. 250).

In Dawkins’ conceptualization, a meme is a symbolic aspect of culture that can, as quoted above, spread via imitative replication, and may represent a variety of things ranging from tunes and ideas to pottery methods and fashion (1976). Social media-related memes, or Internet memes specifically, are a disambiguation of Dawkins’ definition of cultural memes even though they too spread virally ( Shifman, 2011 ). Internet memes as popularly known today were not only supercharged by the Internet, but the use of the term is a co-option and simplification of Dawkins’ broader and nuanced characterization of cultural memes ( Knobel & Lankshear, 2006 ; Shifman, 2014 ). Here, Internet memes represent a narrow category of amateur audiovisual material or images and graphics with or without superimposed text ( Davidson, 2009 ; Milner, 2012 ). There is robust debate about equating to or differentiating Internet memes from traditional memes ( Davidson, 2009 ; Grundlingh, 2018 ; Milner, 2012 ), but that is beyond the scope of this article. Because the current study examines Internet memes, the definition and use of the term meme in this study are limited to those consisting of images and superposed text, much like the definition used in studies such Beskow, Kumar, and Carley (2020) .

Generally, this study examines the credibility and persuasiveness of memes using source credibility as the theoretical framework. Particularly, the study seeks to find whether: (a) expert source attribution in a meme affects its credibility and persuasiveness; (b) the message tone of a meme (objective vs. subjective) affects its credibility and persuasiveness; (c) there is a correlation between the credibility of a meme and its persuasiveness and (d) there is a correlation between the age (of a user) and the credibility and persuasiveness of a meme.

This study contributes to our understanding of the persuasiveness and credibility of online phenomena in the following ways. First, and as mentioned, memes have diffused rapidly within online communication, and it is important to examine the related dynamics. By 2019, memes were second among the types of content most likely to be shared by Gen Z and Millennial Internet users. Here, 66% of this demographic reported that they were either somewhat or very likely to share memes online. Additionally, 54% of this group reported that they were likely to share memes they had created themselves ( Tankovska, 2021 , para. 1). By 2021, memes were the third most shared content in the United States among all demographics, a trend partly driven by the COVID-19 pandemic ( Enberg, 2021 , para. 2). These trends could explain why memes now spread faster and wider than any other nonmeme online content ( Beskow et al., 2020 ).

Additionally, memes emerged as unique communication tools during the COVID-19 pandemic. Users used memes to cope with pandemic-related stress ( Myrick, Nabi, & Eng, 2021 ) as well as to blunt the impact of risk messages and to gain a feeling of control during the crisis ( Flecha Ortiz, et al. 2021 ). The City Baltimore Health Department also famously used humorous memes to encourage young people to get COVID-19 vaccines and to combat misinformation ( Elwood, 2021 ). Conversely, users have used memes to spread misinformation about the coronavirus ( Spencer, 2021 , para. 2), its origins ( Glǎveanu & de Saint Laurent, 2021 ), and to spread a host of anti-vaccine falsities ( Ellis, 2021 ; Goodman & Carmichael, 2020 ).

The third reason relates to the emergence of social media as a conduit for disinformation and misinformation. This includes the fake news campaign during the 2016 U.S. presidential election ( Allcott & Gentzkow, 2017 ; Gunther, Beck, & Nisbet, 2019 ) and a variety of conspiracy movements that emerged thereafter, such as Pizzagate ( Robb, 2017 , para. 2) and QAnon ( Roose, 2021 , para. 3). During the COVID-19 pandemic, social media again proved to be fertile ground for disinformation and conspiracies. One such is the YouTube and Twitter-driven “film your hospital” campaign that alleged that hospitals were empty and not overwhelmed with COVID-19 patients ( Ahmed, López, Vidal-Alaball, & Katz, 2020 ). Another is the viral pseudo-documentary “Plandemic,” which promoted a variety of falsehoods about the coronavirus and vaccines ( Pappas, 2020 ). Similar social media-driven disinformation campaigns have questioned the origin of the coronavirus, its spread patterns, its treatments and vaccines, and the credibility of health experts ( Basch, Meleo-Erwin, Fera, Jaime, & Basch, 2021 ; Su, 2021 ). As mentioned, some among these misinformation campaigns have specifically used memes to spread similar falsehoods ( Reuters Fact Check, 2021 ; Sapienza, 2021 ; Spencer, 2021 ) and therefore it is important to examine the role of memes in such developments. Lastly, few (Internet) meme studies have taken an experimental approach to analyze effects at the time of writing (see Myrick et al., 2021 ). This study addresses this shortcoming by using a multi-stimuli experimental design to examine the effect of COVID-19-related memes.

As mentioned, the word meme derives from Dawkins’ characterization of cultural artifacts that convey ideas, attire, phrases, or ideas and ways of doing things (1976). In contemporary use however, an Internet meme is “a group of digital items sharing common characteristics of content, form, and/or stance, which … were created with awareness of each other, and … were circulated, imitated, and/or transformed via the Internet by many users” ( Shifman, 2014 , p. 41). In this sense, the content refers to the idea expressed by a meme. Form refers to the physical manifestation of the meme such as voice, video, image, or animation. Stance refers to the position on an issue that the meme creator intends to convey with the meme’s message. The current study examines how the content and stance of a meme affects its credibility and persuasion. See Figures 1–4 for examples of prominent Internet memes.

Tourist guy. This early meme is a digitally manipulated hoax depicting a tourist on the World Trade Center observation desk supposedly during September 11 attacks. Form: Photo.

Dancing pall bearers. Derived from a Ghanaian funeral dance, this meme is commonly used to mock people who flirt with deadly situations. Form: Video or animated GIF.

Smudge the cat. This viral photo of a Canadian cat named Smudge has been edited to include a variety of phrases as well as mash-ups with other photos. Form: Photo with text.

The Fake Lincoln quote. This obviously misleading meme is in a class of memes that use an image of famous person with an erroneous quote attributed to him/her. Form: Photo and text.

Despite the rapid diffusion of memes in contemporary online communication, there is a dearth of experiment-based research examining the effect of memes on users. Most pertinent research has taken a sense-making approach in trying to understand the dynamics of meme-based communication, while other research has taken a critical approach regarding the role of memes in communication and society. Even without experiment-based meme studies, existing research suggests such effects. For instance, scholars have discussed how meme humor may belie or lead to nefarious behavior. An example is Durham’s (2018) discussion of the ethical aspect of memes, where some viral memes started out as an exercise in casual curiosity but devolved into morbid curiosity. Such was the case with the viral photo of drowned Syrian refugee child Alan Kurdi. Users later edited the photo, not just into pro-refugee memes, but later into jocular memes that make light of his death. Meme humor may also belie sexism, misogyny, or racial prejudice, some of which may be targeted toward specific individuals or even at an entire group of people ( Dickerson, 2016 ; Drakett, Rickett, Day, & Milnes, 2018 ; Harlow, Rowlett, & Huse, 2020 ).

Not all usage of memes suggests negative effects, and memes may play a positive role. Case in point is Schonig’s (2020) analysis of aesthetic memes and how users did not just react to them as they would other viral Internet content. Here, users delved into philosophical discussions of the meme content, some of which would otherwise have seemed to be mere images or photos. This echoes Shifman’s (2011) analysis of YouTube memes where users inserted their own text onto video clips to create creative dialog. Similarly, Reddit’s MemeEconomy users creatively deploy stock market lingo to discuss meme attributes and the risks and benefits involved in “investing” in the memes. The result is an organic and active community engaged in political and cultural criticism ( Literat & van den Berg, 2019 ).

Scholars have also examined the role of memes in political dialog. This includes the use of memes to deconstruct colonialism ( Frazer & Carlson, 2017 ), using meme humor to discuss political corruption ( Bebić & Volarevic, 2018 ), and even the cult worship of authoritarian leaders ( Fang, 2020 ). Other research indicates that memes may drive protest ( Davis, Glantz, & Novak, 2016 ), engender online radicalization ( Kearney, 2019 ), influence popular perception of future technological trends ( Frommherz, 2017 ), encourage the disclosure of personal experiences ( Vickery, 2014 ), and some memes may be weaponized against institutions such as the media as is done with the popular “fake news” memes ( Smith, 2019 ). Even though the aforementioned meme-based research did not delve much into the effects of memes on users, the literature suggests that such effects are not only apparent, but likely exist and remain to be uncovered, and thus the current study.

This study examines the credibility of Internet memes as well as their persuasiveness in eliciting or changing user behavior. The key variables under study are credibility and persuasion , regarding the believability of the memes (credibility), and the likelihood of that credibility to elicit such behavior as sharing, commenting on, and liking memes (persuasion). Even though social media research generally classifies sharing, commenting, and liking as measures of engagement, research also shows that these actions have a persuasive angle. For instance, commenting and liking has been linked to increased political efficacy and political expression, even among those initially averse to political discussion ( Mutsvairo & Sirks, 2015 ; Yu, 2016 ). Influential social media users also actively persuade others, not just by posting information in general, but specifically by liking and sharing memes created by others ( Weeks et al., 2017 ). Also, comments posted in support of some online health-related PSAs have been shown to elicit real-life behavioral changes ( Shi, Messaris, & Cappella, 2014 ), as were health-related Twitter posts and related retweets ( Lauricella & Koster, 2016 ). Additionally, how a user frames a social media post affects both the credibility and persuasiveness of the message ( Wasike, 2017 ).

Research also indicates that credibility and persuasion are related ( Smith, De Houwer, & Nosek, 2013 ; Wasike, 2017 ; Westerwick, 2013 ). Persuasion is any type of message that will “cause a person or group to adopt as their own a product, person, idea, entity, or point of view that the person would otherwise not support” ( Preston, 2005 , p. 294) or “any non-coercive inducement of individual or collective choice by another” ( Barker, 2005 , p. 376). Credibility refers to how audiences deem a source to be believable and trustworthy and the extent to which they deem the message communicated to be accurate and valid ( O’Keefe, 1990 ; Rice & Atkins, 2001 ).

Like any other form of communication, social media content, including memes, may depend on its credibility and persuasion. An abundance of research supports this. For instance, attitude homophily with political-oriented Facebook messages, or how people think alike on certain issues, positively correlates with perceptions of credibility about the source of the message. This then leads to behaviors such as such as donating, volunteering, and even voting for the source, who in the said study was a political candidate ( Housholder & LaMarre, 2014 ). The current study examines how message homophily, or one’s stance on masks and vaccines affects the credibility and persuasiveness of a meme.

Research also shows that expert sources elicit more credibility than novice or nonexpert sources ( Lin, Spence, & Lachlan, 2016 ; Sohn & Choi, 2019 ). Additionally, users who perceive themselves to be more aligned with others within their social media group are more likely to share this information with others ( Sohn & Choi, 2019 ). Likewise, users who deem themselves to be like the source (of a message) based on online characteristics such as the avatar, may perceive more credibility from an accompanying message ( Spence, Lachlan, Westerman, & Spates, 2013 ). The current study also examines these variables, namely, source expertise, message homophily (as stance on mask-wearing and vaccines) and the likelihood to share memes (as persuasion).

User-generated content is a unique characteristic of Internet-based media ( Wunsch-Vincent & Vickery, 2007 ). Sharing online content such as memes falls under a class of participatory behavior called participant sharing. This is when users not only consume media, but also generate their own content and share it. Additionally, the quality of the content may affect such sharing ( Dedeoglu, 2019 ). Participant sharing is related to interactivity, another unique characteristic of social media communication. Interactivity is the ability to “share, co-create, discuss, and modify user-generated content” ( Kietzmann, Hermkens, McCarthy, & Silvestre, 2011 , p. 241). Research shows that interactivity also positively correlates with credibility ( Li & Suh, 2015 ). User-generated content and participatory sharing are uniquely important to the current study because as mentioned, users may edit photos, images, and videos to create customized memes to share with others ( Dickerson, 2016 ; Drakett et al., 2018 ; Durham, 2018 ).

Research also shows that perceptions of credibility on social media can lead to behavior such as increased social media use and increased online expression ( Neo, 2021 ). This means that as users share more of the content that they deem credible, they may become more expressive about their opinions on related issues. While the Neo study focused on political content, it is within reason to suggest that users may share more of memes they trust and even use them to express their opinions on issues such as masks and vaccines. This would be easy to do given the abundance of memes and the ability to edit memes to suit one’s stance on issues ( Enberg, 2021 ; Tankovska, 2021 ). Other research shows that users who generally perceive social media content as credible are likely to allow products placement on their group pages ( Lai & Liu, 2020 ). This suggests that accepting products placement on one’s page may engender the acceptance of other trusted content such as memes shared by others.

The credibility of health information plays a crucial role during the ongoing Covid-19 pandemic given the misinformation campaigns and conspiracies regarding masks and vaccines vis-à-vis efforts to combat these campaigns with credible and persuasive messages. As I described earlier, the “film your hospital” disinformation campaign and the conspiracy-laden pseudo-documentary “Plandemic” are two such examples. While these two may have abated somewhat at the time of writing, similar campaigns have been harder to combat or even eradicate from social media ( Pazzanese, 2020 ; Rasmus, Fletcher, Newman, Brennen, & Howard, 2020).

Meanwhile, anti-mask campaigns have taken a political bent ( Aratani, 2020 ) and mask-wearing enforcement has sometimes ended in violence and death ( Bromwich, 2020 ; Elfrink, 2021 ). Vaccine hesitancy and denial have also posed problems during various COVID-19 vaccine rollout initiative. This is evident with the nonuniform positive opinions of vaccines across the world. Such opinions vary from 63% worldwide ( Johns Hopkin’s, 2021 ), 72% in the United States ( Funk & Tyson, 2021 ), 79% in Africa ( Africa CDC, 2020 ), 88.9% in China, and a low 27% in Poland ( Lazarus, 2021 ). The vaccine acceptance issue is compounded by longstanding anti-vaccine sentiment ( Hussain, Ali, Ahmed, & Hussain, 2018 ; Royal Society for Public Health, 2019 ).

With the urgency created by the COVID-19 pandemic, government agencies and non-for-profits have launched campaigns to combat this misinformation and improve vaccine acceptance by incorporating the Internet, social media, and related apps ( Harting, 2021 ; Simms, 2021 ). These efforts may well prove effective because recent scholarly studies show that social media plays a critical role in fighting misinformation and improving vaccine acceptance rates ( Kolff, Scott, & Stockwell, 2018 ; Wilson & Wiysonge, 2020 ). However, and as I discuss below, the credibility of these social media and Internet-based campaigns will play a major role in their success because credibility uniquely affects the reception of online health information.

One such uniqueness is the expertise of the source, which has been shown to affect credibility more in an online than an offline context ( Yang & Beatty, 2016 ). The credibility of online health information is also subject to the level of deliberation and verification a user engages in when reading the information. This means that activities such as checking evidence, making comparisons, and evaluating the quality of online health information affects how one perceives the credibility of that information, with younger people more likely to engage in this type of elaboration ( Liao & Fu, 2014 ). This makes age a mediating variable regarding the credibility of online health information, and research supports this.

Generally, young people use the Internet and related technologies such as apps and social media at higher rates than other age groups ( Pew, 2021 ; Vogels, 2019 ). Also, the Internet has traditionally been young people’s go-to source for online health information ( Percheski & Hargittai, 2011 ). This may explain why young people are more confident with online searches for health information and less concerned about associated risks to privacy ( Oh & Kim, 2014 ). It may further explain why young people rate the credibility of online health information the same regardless of the sensitivity of the said information, with no difference for instance, when evaluating highly sensitive (sexually transmitted disease-related) information versus less sensitive (allergy-related) information ( Kim & Syn, 2016 ). Prior use of health apps is also another age-related determinant of online health information credibility ( Cho, Lee, & Quinlan, 2015 ). Also, young people uniquely tend to rate expert sources with more (online) likes accompanying the said information as being more credible than those with less likes ( Borah & Xiao, 2018 ).

H1a: Memes with an expert source attribution will elicit higher credibility than memes without an expert source source attribution. H1b: Memes with an expert source attribution will elicit more persuasiveness than memes without an expert source attribution. H2: There is a positive correlation between the credibility of a meme and the persuasiveness of a meme. RQ1: Does the stance of a subject (pro- or anti-mask/vaccine) affect the credibility and persuasiveness of a meme? H3a: There is an inverse correlation between age and the credibility memes. H3b: There is an inverse correlation between age and the persuasiveness of a meme. RQ2: Is there a significant difference in credibility and persuasiveness between pro-mask/vaccine memes and anti-mask/vaccine memes?

In addition to examining the effect of source expertise and age on credibility and persuasion, this study also examines the effect of message tone on credibility and persuasion. Message tone is a uniquely important variable to this study. First, research shows that social media has a dark side where some users deploy uncivil content to harass, bully, and ridicule others, and often with negative outcomes for the victims ( Gearhardt & Zhang, 2014 ; Sobieraj, 2018 ; Whittaker & Kowalski, 2015 ). To do this, some users strategically repurpose objective and fact-based information into biased uncivil messages that fit a certain narrative, either to support or oppose an issue. Masullo, Lu, & Fadnis (2021) study of civil and uncivil, pro- and anti-issue online comments is a good example of such. See below for excerpts from that study (p. 3401). The study found that uncivil comments, some shown in the excerpts below, not only affected some readers emotionally, but the comments also affected the likelihood of some readers to speak out about the issues. The current study used similar messaging to develop the message tone in the memes used as stimuli for the experiment.

Excerpts of objective and subjective online comments

H4a: Memes with an objective message tone will elicit higher credibility ratings than memes with a subjective message tone. H4b: Memes with an objective message tone will elicit more persuasiveness than memes with a subjective message tone.

This study used a 2 × 2 × 2 experimental design. Factor one was source (expert vs. nonexpert), factor two was messaging tone (objective vs. subjective), and factor three was the message type in a meme (pro- or anti-mask/vaccine). All factors were within group designs. Data were collected between 14 July and 21 July 2021. The study was approved by the institutional review board.

I created a set of eight memes from scratch, using Photoshop, each to represent one of the eight conditions in the experimental design. The memes were created to accurately mimic real-life memes on Twitter regarding visual style, quality, and account details such as usernames and statistics such as followers, retweets, likes, etc. See Appendices A and B for the stimuli and Table 4 for the eight treatment conditions. I chose the U.S. Centers for Disease Control as the expert source because it is a widely recognized organization in the United States. The nonexpert source was fashioned as a fictitious activist political action committee, the Patriots for Liberty PAC.

Means of Meme Credibility and Persuasiveness for the Stance/Message Combinations a

Standard deviations shown in parentheses

Repeated measures ANCOVA (using stance as a covariate) for credibility with a Greenhouse–Geisser correction ( F [2.88, 3,349.02] = 292.01, p < .001; η p 2 = 0.20).

Repeated measures ANCOVA (using stance as a covariate) for persuasion (with a Greenhouse–Geisser correction F [3.29, 3920.16] = 216.70, p < .001; η p 2 = 0.15).

Participants

Subjects were drawn randomly from a Qualtrics panel representative of U.S. adults regarding demographics such as age, gender, and political affiliation. All subjects were social media users. Qualtrics panels and similar others are an oft-used sampling source and their validity in data collection is proven ( Brandon, Long, Loraas, Mueller-Phillips, & Vansant, 2014 ; Gil de Zúñiga, Barnidge, & Scherman, 2017 ; Holt & Loraas, 2019 ; Kalmoe, Gubler, & Wood, 2018 ).

Instrument and procedure

After consenting to the study, subjects answered a pair of questions that queried their stance on masks and vaccines—see a sample question in the next section. Subjects then answered a series of questions measuring the variables discussed in the next section. A rating scale of 0–10 (0 = no support at all, 10 = fully support) was used. The zero in the scale was used to account for subjects who were diametrically opposed to mask-wearing and/or vaccines. See Appendix C for instrument. Subjects were emailed a link to the survey. Even though all subjects viewed all eight stimuli, the stimuli were presented one at a time and randomly to reduce order effects. Subjects viewed each stimulus and immediately an instrument before proceeding to the next stimuli and filling the accompanying instrument.

The five independent variables were expert source, message type, message orientation, subject stance (on masks and vaccines), and age. The dependent variables were credibility and persuasion.

You just saw a meme on Covid-19 vaccines from the Centers for Disease Control (CDC), a federal agency responsible for public health and safety. Please indicate your response to the following statements on a scale of 0–10 where: 0 = Totally disagree and 10 = totally agree. You just saw a meme on vaccines from Patriots for Liberty, an activist political action committee. Please indicate your response to the following statements on a scale of 0–10 where: 0 = Totally disagree and 10 = totally agree.

On a scale of 0–10 where: 0 = fully opposed to and 10 = fully support, how would you characterize your support for mask-wearing in public (or Covid-19 vaccines) as a measure to control the coronavirus?

Message tone. Research indicates that online health information that makes subjective claims elicits less credibility than that which is objective ( Gao et al., 2015 ). This variable measured the effect of the objectivity or subjectivity of a meme’s message on its credibility and persuasiveness. Objective messaging included memes that made levelled claims and subjective messaging included memes that make speculatory and inflammatory claims and distorted facts (See appendices A and B for examples). I used messaging patterns similar to Masullo, Lu, & Fadnis (2021) when creating the memes used as stimuli.

Message orientation. This variable distinguished among pro- and anti-mask and pro- and anti-vaccine memes. See Table 1 and Appendices A and B for details.

Comparisons of Means of the Persuasion Parameters a

Standard deviations are shown in parentheses.

p < .001

Age . As discussed, research shows that younger people rate online and social media stimuli different from other age groups. This variable measured the effect of age on the perceptions of meme credibility and persuasiveness.

Credibility . This variable was measured by a set of eight questions derived from previous studies ( O’Keefe, 1990 ; Rice & Atkins, 2001 ; Tandoc, 2019 ; Wasike, 2017 ). Each question queried the subjects on each of the eight credibility parameters. These were sincerity, honesty, trustworthiness, expertise, effectiveness, reliability, message comprehension, and accuracy. A composite credibility score was then computed based on the mean of the responses to the eight questions.

Persuasion. This variable measured the effect of a meme on subjects regarding how it persuaded them to share it, comment on it, or post a like on it. The variable was measured by three questions derived from previous studies ( Li & Suh, 2015 ; Neo, 2021 ). See Appendix C for sample question. The three questions that asked users about their likelihood to (a) Like the meme, (b) Comment on the meme and (c) Post or retweet the meme on their social media accounts. Like credibility, this also used a 0–10 scale and a composite persuasion score was then computed based on the mean of the responses to the three questions.

Stimuli pretest

A stimulus pre-test was conducted with a nonrandom pilot sample ( N = 79) based on a set of memes depicting only mask-related messages. Subjects received an email with a Qualtrics survey link that contained the stimuli and instrument. Subjects viewed four memes that depicted respectively: an objective pro-mask meme, a subjective pro-mask meme, an objective anti-mask meme, and a subjective anti-mask meme. Exposure was done one meme at a time and in random order to avoid order effects. Subjects viewed and responded to each meme before moving to the next.

Overall, the Cronbach alphas for the reliability of the various credibility and persuasion scales ranged from 0.82–0.95. Memes with an expert source elicited higher credibility ( M = 8.16, standard deviation (SD) = 2.06) than those with a nonexpert source ( M = 4.9, SD = 3.10, p < .001, t = 7.45, d = 0.92). Expert-sourced memes also elicited more persuasion ( M = 5.39, SD = 3.18) than nonexpert sourced memes ( M = 3.75, SD = 3.36, p < .001, t = 3.47, d = 0.42). Likewise, memes with an objective message ( M = 6.60, SD = 1.93) elicited more credibility than memes with a subjective message ( M = 5.22, SD = 1.79, p < .001, t = 5.01), and were also more persuasive ( M = 4.62, SD = 2.67) than those with a subjective message ( M = 3.27, SD = 2.17, p < .001, t = 4.61).

I used G*Power to determine the appropriate sample size for the main study. G*Power is a widely used power analysis software for determining effects and sample sizes ( Faul, Erdfelder, Lang, & Buchner, 2007 ; Faul, Erdfelder, Buchner, & Lang, 2009 ; Lakens, 2013 ). I used the two Cohen’s d effects sizes reported above as the a priori criteria, respectively. The analysis indicated that samples sizes of either N = 36 (for credibility) or N = 47 (for persuasion) were appropriate for the paired samples tests used in this study (80% power, alpha = 0.05, two-tailed).

This study used a nationally representative random sample of U.S. social media users ( N = 1,200). The sample was 49.3% female, 49.1% male, and 1.2% nonbinary. Of all respondents, 65.6% were non-Hispanic white, 12% were non-Hispanic Black, 12.3% were Hispanic, 5% were Asian, 3.2% were Native American, and 0.6% were Native Hawaiian or Pacific Islanders. The average age was 44.94 years.

Data supported all hypotheses. Because all subjects viewed all eight same stimuli (in random order to avoid order effects), paired sample t -tests and repeated measures Analysis of Covariance (ANCOVA - with stance as a covariate) were used for data analysis, an approach suitable for the within-subjects-only design used in this study. Hypothesis one predicted that memes with expert source attribution would garner more credibility as well as be more persuasive than those with a nonexpert source. Data showed that overall, memes with an expert source elicited more credibility ( M = 7.03, SD = 2.62) than those with a nonexpert source ( M = 4.91, SD = 3.05, p < .001, t = 18.87; d = 0.55). Likewise, memes with an expert source were more persuasive ( M = 5.46, SD = 3.27) than those without a nonexpert source ( M = 4.03, SD = 3.47, t = 15.02, d = 0.44). Because all expert-source memes were also pro-mask/vaccine and all nonexpert-source memes were also anti-mask/vaccine, these results also show that overall, pro-mask/vaccine memes were more credible and persuasive than anti-mask/vaccine memes. Additionally, because the persuasion variable was measured by three questions (about liking, commenting, and sharing memes), it is worth examining the differences among the three parameters (See Table 1 ).

Hypothesis two predicted a positive correlation between the credibility and persuasion of the memes, and data supported this prediction ( r = 0.78, p < .001). Because this correlation refers to all memes in general regardless of their message on masks and vaccines, it is insightful to consider the stance (on masks and vaccines) of the subjects viewing the memes. Therefore, RQ1 queried about the correlation between a subject’s stance (on masks/vaccines) and the credibility and persuasion of the memes, respectively. To answer this research question, the stance (on masks and vaccines) variable was split into two categories—low support for masks/vaccines (5 and below on the 0–10 scale) and high support for masks/vaccines. The correlation between credibility and persuasion among the high mask/vaccines support group remained steady ( r = 0.79, p < .001) but that for the low mask/vaccines support group declined ( r = 0.62, p < .001).

Even then, these results still reflect all meme types, so further analysis was conducted to determine the correlation between stance and the eight combinations of memes. This analysis was done for credibility ( Table 2 ) and persuasion ( Table 3 ). As the tables indicate, the only strong correlations to emerge were between stance and the pro-mask/vaccines memes. Additionally, there were significant correlations among pro-mask/vaccine memes as were between anti-mask/vaccine memes. The fact that there were more positive correlations among the anti- and pro-mask/vaccine memes for persuasion may be because one of the persuasion scale questions asked about commenting on memes without specifying whether the comments were critical or laudatory. It is possible that pro-vaccine subjects may have intended to post negative comments on anti-mask/vaccine memes and vice versa, and hence the correlation.

Correlations Between Stance and the Credibility of Memes

Correlation is significant at the 0.01 level (two-tailed).

Correlations Between Stance and the Persuasiveness of Memes

Hypothesis three predicted an inverse correlation between age and the credibility of a meme and the same pattern between age and the persuasiveness of a meme. This hypothesis was partially supported. There was no correlation between age and credibility, but there was a moderate inverse correlation between age and persuasion ( r = −0.18, p < .001), meaning that younger subjects were more likely to like, comment on, and share memes than older subjects. RQ2 queried the differences in credibility and persuasiveness between pro-mask/vaccines memes and anti-mask/vaccines memes. Overall, pro-mask/vaccines memes scored higher in credibility ( M = 7.03, SD = 2.62) than anti-mask/vaccine memes ( M = 4.91, SD = 3.05, p < .001, t = 18.87, d = 0.55). They also scored higher in persuasion ( M = 5.46, SD = 3.27,) than anti-mask/vaccines memes ( M = 4.03, SD = 3.47, p < 0.001, t = 15.02. d = 0.44) (See Table 4 for details).

Overall, memes with an objective tone were more credible ( M = 6.06, SD = 2.12) than those with a subjective tone ( M = 5.87, SD = 2.24, p < .001, t = 5.0, d = 0.16), regardless of whether they displayed a pro- or anti-mask/vaccine message. Objective-toned memes were also more persuasive ( M = 4.83, SD = 3.0) than subjective-toned memes ( M = 4.66, SD = 3.04, p < .001, t = 5.35, d = 0.16), regardless of their pro- or anti-mask/vaccine message, thus supporting hypothesis four. A nuanced examination indicates larger differences when a meme’s pro- or anti-mask/vaccine message is considered. A repeated measures ANCOVA (using stance as the covariate) with a Greenhouse–Geisser correction ( F [2.88, 3,349.02] = 292.01, p < .001; η p 2 = 0.20) returned statistically significant differences among the four possible means for objective (pro- and anti-mask/vaccine) and subjective (pro and anti-mask/vaccine) messaging, with objective pro-mask/vaccine memes scoring the highest credibility ( M = 7.07, SD = 2.68). Memes with a subjective anti-mask/vaccine message earned the lowest credibility ( M = 4.75, SD = 3.31).

The same results emerged for the persuasiveness of the memes. A repeated measures ANCOVA (using stance as the covariate) with a Greenhouse-Geisser correction ( F [3.29, 3920.16] = 216.70, p < .001; η p 2 = 0.15) returned significant differences among the four persuasion means. Here, pro-mask/vaccine memes with an objective tone were the most persuasive ( M = 5.49, SD = 3.35, F [1.46, 1737.87] = 188.35, p < .001), while memes with a subjective anti-mask/vaccine message were the least persuasive ( M = 3.89, SD = 3.62). Because each of the credibility and persuasion means in these ANCOVA results combine anti- and pro-mask/vaccine messages, Table 4 shows nuanced results for the eight combinations of experimental conditions for credibility and persuasion for all pro- and anti-mask/vaccines memes.

This study examined COVID-19-related memes regarding their credibility and persuasiveness based on pro- and anti-mask/vaccine messages. A major contribution this study makes to literature is that it takes an experimental approach to examine meme-based communication. First, the experimental approach identified when, where, and how the memes affected credibility and persuasion, and the extent and direction of these effects. Also, as I discussed earlier, few if any Internet meme-communication studies have yet taken an experimental approach. Most existing research is largely descriptive and/or analytical. An experimental approach is a methodological contribution to pertinent research. Also, this study is timely given that data collection occurred during a confluence of the rapid diffusion of meme-based communication and the COVID-19 pandemic. This is opportune given the roles that social media in general, and meme-based communication have played among issues such as vaccine promotion campaigns, vaccine and COVID-19 misinformation campaigns, and the campaigns aimed at combatting this misinformation during the pandemic.

The results indicate that like other social media content, memes do have a discernible effect on users. Additionally, there are discernible patterns within meme-based communication, despite the seemingly ubiquitous and rapid diffusion of memes in contemporary communication. One such pattern is that the source of a meme determines how credible users view the meme and how likely they are to like, comment on, or share it with others. Memes from expert sources are more likely to be believed and shared. This matches existing research on social media credibility and content sharing ( Lin et al., 2016 ; Sohn & Choi, 2019 ; Spence et al., 2013 ), and specifically research on online health information ( Yang & Beatty, 2016 ). Similarly, age correlates inversely with the likelihood to like, comment on, and share memes, a reflection of the unique age-related communication patterns in social media communication in general ( Pew, 2021 ; Vogels, 2019 ) and online health communication specifically ( Borah & Xiao, 2018 ; Cho et al., 2015 ; Liao & Fu, 2014 ; Oh & Kim, 2014 ).

This expert source and age-related findings have unique policy implications. At the time of writing, young people and young adults are among the demographics least likely to get Covid-19 vaccines ( Baack, 2021 ; Thigpen & Funk, 2020 ). Meanwhile, research indicates that online sources are the go-to venues for health information among young people ( Pew, 2021 ; Vogels, 2019 ). Young people also do more information verification (via comparisons and evidence-checking) as a means of determining the credibility of the online health information ( Liao & Fu, 2014 ) than other demographic groups do. Additionally, young people are more adept at navigating the Internet ( Oh & Kim, 2014 ) and are more likely to use social media metrics to determine the credibility of online information ( Borah & Xiao, 2018 ). As discussed, memes provide simple and easily comprehensible visual messages, and this fact alone may enhance their credibility regardless of the target demographic ( Harvey, 2020 ; Sadoski & Paivio, 2013 ; Trethewey et al., 2020 ). The combination of these facts suggests that meme-based social media campaigns from credible sources such as the CDC may be an effective way to reach vaccine-wary young people.

It worth mentioning that this study used a unidimensional credibility scale. Other scholars have used similar, but multidimensional scales that differentiate the credibility of the author and that of the information itself ( Yin & Zhang, 2020 ; Xu et al., 2021 ). To account for this nuance, I ran further analysis with a two-dimensional version of the original scale to test for credibility parameters based on the author-only parameters (sincerity, honesty, trustworthiness, and expertise) and information-only parameters (reliability, effectiveness, comprehension, and accuracy). Repeated mesures ANCOVA (with stance as a covariate) returned similar results as those of the unidimensional scale for the credibility of pro- and anti-mask/vaccine memes. Those memes with an expert source attribution still elicited more author- and information-only credibility than nonexpert sourced memes. See Tables 4 and 5 for comparisons.

Means of Author- and Information-Only Credibility a

Repeated measures ANCOVA (using stance as a covariate) for author-only credibility with a Greenhouse–Geisser correction ( F [3.0, 3351.40] = 275.43, p < .001; η p 2 = 0.19).

Repeated measures ANCOVA (using stance as a covariate) for information-only credibility with a Greenhouse–Geisser correction ( F [3.05, 3594.60] = 276.80, p < .001; η p 2 = 0.19).

Another important finding has to do with the objective versus subjective tone of meme messages. The study found that objective-toned memes were more credible and persuasive than subjective-toned memes. This was true among both pro- and anti-mask memes, with objective pro-mask memes being the most credible and subjective anti-vaccine memes being the least credible. This is noteworthy in the context of social media communication and the accompanying incivility and toxicity ( Anderson & Huntington, 2017 ; Kosmidis, 2020 ; Rheault et al., 2019 ). Also, the literature discussed earlier shows that meme-based communication may engender negative communication. For instance, humorous memes but with subjective messages may belie negativity ( Dickerson, 2016 ; Durham’s, 2018 ; Harlow et al., 2020 ). Memes may also promote prejudice and radicalization ( Drakett et al., 2018 ; Kearney, 2019 ) and even be weaponized against institutions such as the media ( Smith, 2019 ). The objective versus subjective dynamic is a unique finding given that the mask-wearing debate has exacerbated the toxicity and incivility of social media communication ( Pascual-Ferrá, Alperstein, Barnett, & Rimal, 2021 ). The fact that subjects placed higher credibility on objective memes rather than subjective memes and were more likely to share objective memes bodes well for the promotion of civil discourse on social media, especially regarding such contentious issues as mask-wearing and COVID-19 vaccines.

As with any research endeavor, this study comes with limitations. One limitation is that the study uses data from a self-reported survey, albeit from a random and representative sample. As with any survey-based study, issues of desirability responses must be considered, especially when querying subjects about contentious issues such as mask-wearing and COVID-19 vaccines. However, the high reliability scores for the survey scales used in the study should mitigate this concern. Additionally, the successful stimuli check improves the validity of the results. Another consideration is that the subjects were examined in an experimental situation and were exposed only to one meme at a time. On social media users may view several memes as well as other content such as posts, comments, and multimedia. This limitation is closely related to those which are natural to most single-scenario experimental studies like this one. Unique and unrecognized conditions such as heightened emotions, differences among subjects, and different environments may impact data validity and affect the generalization of the results ( Collett & Childs, 2011 ; Ferrara & Yang, 2015 ; Funke, 1998 ; Jackson & Jacobs, 1983 ). Additionally, the pairs of contrasting memes were visually identical expect for the textual information. If, during random exposure, a savvy subject viewed the same images sequentially, they could have guessed the hypotheses, and such an occurrence increases the chances of desirability responses. The data should be considered with this issue in mind.

The also study compared the CDC, a well-known federal agency, to a fictional PAC. Even though the CDC has registered low approval ratings lately ( Jones, 2021a , 2021b ), it still carries the name recognition that the nonexpert source used here does not. Therefore, the results reported in this study should be interpreted within this lens. Important also is that the study did not consider ideology and its interactions with the variables examined, given the fluidity and uncertainty of COVID-19-related research during data collection. Recent research suggests an ideological impact on COVID-19 vaccine hesitancy ( Bhochhibhoya, Thapaliya, Sharma Ghimire, & Wharton, 2021 ; Galston, 2021 , para. 4; Haytko & Taillon, 2021 ), and future research may examine the role of ideology in the credibility and persuasiveness of pro- and anti-mask/vaccine memes.

Despite these limitations, the study makes practical and theoretical contributions. A practical contribution has to do with systematically showing that memes play a crucial role in public health communication and campaigns, and specifically regarding mask-wearing and vaccine hesitancy. Data showed that expert-sourced memes with objective messages are best poised to improve mask-wearing and vaccine acceptance. As I mentioned, the CDC and other public health agencies may be well served by incorporating meme-based communication when promoting mask-wearing and Covid-19 vaccines. Data suggests that this may uniquely improve messaging targeted towards young people who are currently one of the most COVID-19 vaccine-adverse demographic groups.

The study also makes theoretical contributions. As I mentioned, it enhances meme-based communication by taking an experimental approach using a multi-stimuli design. In the future, scholars may adopt and improve on this design. The study also examined a unique set of variables, and the results and interactions reported here not only add to knowledge, but scholars may also retest and improve on the variables. Because this study examined phenomena related to the COVID-19 pandemic, it also adds to crisis communication research generally and specifically to crisis communication research vis-à-vis meme-based communication. Lastly, by examining message tone, the study adds to previous works that have examined hostility and incivility in online communication.

This study was funded by the Henry W. Hauser and Margaret H. Hauser Endowment, Department of Communication, College of Liberal Arts, at the University of Texas Rio Grande Valley.

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Pro-mask meme with objective message (expert source).

Anti-mask meme with objective message (nonexpert source).

Pro-mask meme with subjective message (expert source).

Anti-mask meme with subjective message (nonexpert source).

Pro-vaccine meme with objective message (expert source).

Anti-vaccine meme with objective message (nonexpert source).

Pro-vaccine meme with subjective message (expert source).

Anti-vaccine meme with subjective message (nonexpert source).

You just saw a meme on COVID-19 vaccines from the Centers for Disease Control (CDC), a federal agency responsible for public health and safety. Please indicate your response to the following statements on a scale of 0–10, where 0 = totally disagree and 10 = totally agree.

You just saw a meme on vaccines from Patriots for Liberty, an activist political action committee. Please indicate your response to the following statements on a scale of 0–10, where 0 = totally disagree and 10 = totally agree.

The author of the information is sincere.

The author of the information is honest.

The author of the information is trustworthy.

The author has expertise on the issue.

The arguments are conveyed effectively.

This information provided is reliable.

The information is easy to understand.

The information provided is accurate.

Please indicate your response to the following statements on a scale of 0–10, where 0 = not at all likely and 10 = very likely.

How likely are you to:

Like the meme?

Reply to the meme?

Post or retweet the meme?

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Dank or not? Analyzing and predicting the popularity of memes on Reddit

• Kate Barnes 1 , 2 ,
• Tiernon Riesenmy 1 , 3 ,
• Minh Duc Trinh 1 , 4 ,
• Eli Lleshi 1 , 5 ,
• Nóra Balogh 1 , 6 &
• Roland Molontay   ORCID: orcid.org/0000-0002-0666-5279 1 , 7 , 8  

Applied Network Science volume  6 , Article number:  21 ( 2021 ) Cite this article

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Internet memes have become an increasingly pervasive form of contemporary social communication that attracted a lot of research interest recently. In this paper, we analyze the data of 129,326 memes collected from Reddit in the middle of March, 2020, when the most serious coronavirus restrictions were being introduced around the world. This article not only provides a looking glass into the thoughts of Internet users during the COVID-19 pandemic but we also perform a content-based predictive analysis of what makes a meme go viral. Using machine learning methods, we also study what incremental predictive power image related attributes have over textual attributes on meme popularity. We find that the success of a meme can be predicted based on its content alone moderately well, our best performing machine learning model predicts viral memes with AUC=0.68. We also find that both image related and textual attributes have significant incremental predictive power over each other.

Introduction

Over the past decade, Internet memes have become a pervasive phenomenon in contemporary Web culture (Laineste and Voolaid 2017 ). Due to their popularity, memes have received considerable attention in areas such as pop culture, marketing, sociology, and computer science (Bauckhage et al. 2013 ; Journell and Clark 2019 ). In the time of the COVID-19 pandemic, memes have become an even more important part of social life since due to social distancing orders more people turned to the Internet for everyday interactions. As a result, Web culture is moving faster than ever and social media sites have exploded with coronavirus memes as people all over the world try to take this serious situation with a pinch of humor (Bischetti et al. 2020 ).

The increasingly participatory nature of the Internet has made memes into a social phenomenon, created, altered, and spread by Internet users themselves. Today, memes are not only a source of humor but also draw attention to poignant cultural and political themes (Brodie 2009 ). Memes tend to reflect pressing global issues and while they are not always loyal to the facts (Simmons et al. 2011 ), they often show what the public is noticing most. Many authors have explored the social network factors that lead a meme to go viral but bracketed the impact that meme content may have on popularity (Gleeson et al. 2015 , 2014 ; Weng et al. 2012 ). In other areas of human achievement viral success is closely linked with merit (Yucesoy and Barabási 2016 ), but it is unclear what characteristics lead a meme to have merit. This paper investigates the relationship between a meme’s content, excluding social network features, and its popularity. Along the way, it exposes what topics were popular on the Internet during the global COVID-19 pandemic.

Our paper joins a growing body of literature that employs network science and data science techniques to predict the popularity of Internet memes (Weng et al. 2012 ; Maji et al. 2018 ; Tsur and Rappoport 2015 ; Wang and Wood 2011 ). Here we analyze the popularity of coronavirus memes based on 129,326 records scraped from Reddit, the largest social news and entertainment site. The main contributions of this work can be summarized as follows:

Using advanced machine learning techniques (such as convolutional neural networks, gradient boosting, and random forest), we perform a content-based analysis of what makes a meme successful, considering several features from both text and image data.

We stand apart from other authors by investigating whether the success of a meme can be predicted based on its content alone, excluding social network factors.

We not only study what makes a meme viral, but we also analyze what incremental predictive power image related attributes have over textual attributes on memes popularity.

Our study provides a looking glass into the thoughts of Internet users during the COVID-19 pandemic.

Related work

The term “meme” precedes the digital age, stemming from the Greek mim-ma, something imitated. Thus, memes are pieces of cultural information that remain relatively unchanged as they are passed between individuals in society through imitation. In the modern age, the term has been co-opted by Internet users to mean snippets of information that self-replicate on the Internet (Dawkins 2016 ; Shifman 2014 ). When memes took the form of hashtags, tweets, photos, quotes or jokes shared repetitively on the web they became highly visible and a common source of data for social computer science researchers. They are transmitted from person to person through social media sites, online news, or blog posts and can reach extremely large audiences in short amounts of time. These viral memes are important, shared social phenomena. They can represent common opinions, cultural norms (Dynel and Messerrli 2020 ), carry political power or motivate social change (Dynel 2020 ; Simmons et al. 2011 ; McClure 2016 ; Du et al. 2020 ). Humorous content may play a crucial role in the spread of memes as it encourages user interaction and creates a sense of in-group connection (Vásquez 2019 ). However, little is understood about what kind of information is so appealing to Internet users as to become viral . Ours is among few studies that places the content of memes under scholarly analysis.

The journey of Internet popularity is commonly framed in network science as competition between memes for limited user attention (Gleeson et al. 2014 , 2015 ). Memes are analogous to genes (Wang and Wood 2011 ), cultural fragments passed down through generations. In itself, the Darwinian frame through which memes are understood recognizes the importance of meme content. However, most studies focus on how memes diffuse through online social networks (Wang and Wood 2011 ) taking into account user interests (Weng et al. 2012 ), memory (Gleeson et al. 2015 ), and other social factors.

Many studies have successfully predicted the viral Internet memes based on social network factors (Maji et al. 2018 ; Weng et al. 2014 ) and others have designed mathematical models that closely align with the actual transmission of memes through the Internet (Weng et al. 2012 ; Wang and Wood 2011 ; Bauckhage 2011 ). Even when measured in many ways, meme popularity displays a long-tailed distribution. Few memes actually become viral, and most are only appreciated by a few tens of people (Gleeson et al. 2015 ). Memes distributed in more diverse and well-connected audiences are more likely to go viral (Weng et al. 2014 ). Additionally, people are more likely to share memes related to content that they have shared in the past (Weng et al. 2012 ). All of these studies put forth neutral models: they assumed no inherent advantage in terms of memes’ attractiveness to individuals.

In addition to social network factors, the content and formatting of a meme can effect its popularity. Tsur and Rappoport ( 2015 ) analyzed hashtags on Twitter, and found that brevity is the most important feature for the memes’ popularity followed by certain legibility characteristics such as capitalization. Berger and Milkman ( 2012 ) found that more emotionally arousing text segments from online news are more likely to go viral . Our analysis of meme captions’ length replicates the finding by Tsur et al. but our meme sentiment analysis differs from the Berger and Milkman finding. Others note that there is ever increasing engagement with political memes among adults on the Internet and express concern that political memes will be used to promote extremism or spread misinformation. According to a recent look at Twitter data, 30 percent of image-with-text memes contain political content (Du et al. 2020 ). There are also disparities among what political and demographic groups share those memes  (McClure 2016 ).

While many papers investigate short text data like hashtags (Tsur and Rappoport 2015 ; Weng et al. 2014 ), quotes (Simmons et al. 2011 ), and Google searches (Wang and Wood 2011 ), few look at the combination image-with-text memes we consider here. Qualitative studies describe the symbols used in meme sub-genres and how their used but do not analyze the impact of these symbols on the memes popularity (Dynel 2016 ; Dynel and Messerrli 2020 ). A study by Bauckhage et. al. models how users’ attention to image-with-text memes fluctuates over time (Bauckhage et al. 2013 ). It shows that evolving memes (slightly different versions of the same meme) are more likely to gain popularity and stay popular for longer. Du et al. ( 2020 ) only study the text within image-with-text memes, claiming that the image is merely a neutral background or further emphasizes information already addressed in the text. Our paper contests this claim. Another study by Khosla et al. investigates the content and social contexts of popular images alone, using data from Khosla et al. ( 2014 ). They found that certain colors, low-level image properties like hue, and represented objects correlate with increased image popularity. However, popularity on a photo-appreciation sight like Flickr is much different than the social undertones that go into memes. In our model, similar features to those considered by Khosla et al. show different relationships to image popularity.

Our study considers the widest array of content-based attributes in image-with-text memes so far. Furthermore, our data represents the intense political moment at the start of the global coronavirus pandemic.

Data description and preparation

All data for this project were collected from Reddit, the so called “front page of the Internet.” More precisely, the image-with-text memes came from the largest meme subreddits, namely r/MemeEconomy , r/memes , r/me_irl , r/dankmeme , and r/dank_meme . The subreddits represent communities devoted to the creation of memes and consequently, the development of a shared sense of humor on Reddit. Most popular Internet content first went viral on Reddit, hence the websites catchphrase, so popular memes from these subreddits are likely representative of the content on many other Internet sites too. Additionally the strict etiquette implemented by the Reddit community and moderators ensures that posts align with the subreddit description (Sanderson and Rigby 2013 ). Thus, only image-with-text memes populate the five subreddits from which we scraped data.

We employed the Pushshift API (Baumgartner et al. 2020 ) to scrape data from posts in the five meme subreddits. In total we scraped 129,326 unique posts from March 17th, 2020 to March 23rd, 2020 which constituted the beginning of the global coronavirus outbreak. For each post we retrieved the features found in lines 1–10 of Table  1 . Additional features such as urls to access the post on Reddit and unique meme ids were scraped as well, but only the features we use for analysis are included in Table 1 . Likewise, the features downvotes, meme awards, and posting author were scraped from Reddit and eliminated early on because they were incomplete, populated mostly with zeros. Many of the features scraped from Reddit metadata were already numerical, such as created_utc and ups. The categorical features is_nsfw and subreddit were one-hot-encoded into a numerical representation.

We further processed the meme images, titles, and text from the images to enrich our feature set with more content-based features. These extracted features are listed in lines 13–22 of Table  1 and discussed in more detail in the “ Models and results ” section. In the process of extracting the content-based features, we made a GET request on each link and observed the status code. Any post with a link that returned a 404 or other similar error was removed from the data set in order to avoid evaluating dead links. Further, any post with a media other than images, such as gifs, was removed as we only wished to consider image-based memes. These cleaning steps resulted in a total of 80,362 records for training and testing the machine learning models. After numerically encoding the image and text based content features that will be discussed in detail in the next couple sections, there were a total of 97 data attributes.

Some conclusions could be made based on the Reddit metadata alone. The created_utc feature contains the timestamp when the post appeared on Reddit in the Coordinated Universal Time zone (UTC). Since most active Reddit users reside in the USA (Tankovska 2020 ), we converted this to North American Central Time Zone. Based on this feature we created a categorical feature representing the time of day, in four hour increments, when the post was created. The bottom subfigure of Fig.  1 shows the effect of time of day on the normalized upvotes that posts received. Posts published on Reddit from midnight to noon Central US time have a higher chance to attract great attention. This result could mean that most upvotes on Reddit are accumulated during the course of the day, in USA time zones. The memes posted during daytime (Central US time) have more chance to receive moderate attention, while memes posted at night are more exposed to extreme events, meaning that receiving very low attention or great attention. The observation that memes posted at night have more chance to be dank is in line with the phenomenon that was observed by Sabate et al. ( 2014 ) based on the analysis of popularity of Facebook content. The authors argue that if content is posted during periods with low user activity (at night), when users will connect in peak hours the post appears at the top of the news wall, that makes it more likely to be liked, commented or shared.

The more subscribers, the more social exposure, so the number of upvotes a post received was likely influenced by the number of subscribers to the subreddit where it was posted. In our data, r/memes has the most subscribers, around 10,000,000, followed by r/me_irl with around 4,000,000, and r/Meme_Economy with around 1,000,000 subscribers; r/dank_meme and r/dankmeme have the least subscribers, less than 500,000 and less than 1000 subscribers respectively. Indeed, we can observe a positive correlation between upvotes and subscribers, as the subreddits with more subscribers tend to get more upvotes (see Fig. 1 upper subfigure). To confirm this observation, we determined the median number of upvotes for each respective subreddit and calculated a Pearson correlation coefficient between these values and the number of subscribers for each subreddit. We received a value of 0.977 for the Pearson correlation coefficient, which indicates a strong near-linear relationship between the upvotes of a post and the number of subscribers to the subreddit. To eliminate this network effect, we normalized the number of upvotes by dividing by the number of subscribers from the respective subreddit where it was posted. In modifying the upvotes feature, we were able to better gauge the popularity of a meme based upon its content alone.

Upper figure shows the number of upvotes for each scraped subreddit. Bottom figure presents the normalized upvotes for each time frame

The viral nature of image-and-text memes on Reddit makes this data well suited for a binary classification task. The distribution of normalized upvotes follows a long-tailed distribution: most memes received few upvotes while few memes received many upvotes as shown in Fig. 2 . Therefore, viral memes usually differ by two or more orders of magnitude from not viral memes, as defined by our binary classification label, called dank or not in Table 1 , and used for the supervised learning models. Using the the normalized upvotes feature as our criteria, any posts with a normalized upvotes value in the top 5% of all posts was classified as dank (positive label, 1), and the rest were classified as not_dank (negative label, 0). Our data set contains 4019 dank entries, and 76343 not_dank entries. Formulating our prediction labels in this way assured that we investigate the phenomenon of viral popularity (rather than moderately successful or mediocre memes) as proposed in the introduction.

We will use three supervised learning models to predict whether memes fall into the dank or not dank categories: gradient boosting, random forest, and convolutional neural network models. The former two use the entire feature set described in Table  1 for training (except the media link feature). The neural network model uses only the meme images, accessed via the media feature, as its input and it is based on a smaller sample of data records. This subset of data will be discussed in more detail in the “ Transfer Learning with convolutional neural network ” section.

The distribution of the normalized upvotes for dank and not dank memes

Models and results

In this section we present the results of our analysis. First, an explanatory analysis is provided for the textual and image related attributes with a focus on the impact they have on meme popularity. We also present feature engineering steps. Next, we briefly describe the applied machine learning models together with their performance in predicting the success of memes.

Text analysis

A large portion of the humor and meaning of memes are contained in the text which appears inside a meme image. This text differs from the caption of the meme which was written by the user who created the post and can be scraped directly from Reddit. Both the caption and the text contained within the meme itself may affect popularity. In this section, we study the predictive power of the attributes derived from the caption and the text extracted from the images on meme popularity.

The text from the images was extracted using Optical Character Recognition (OCR) (a9t9 software GmbH 2020 ). We combined the text obtained by OCR with the caption of the meme, to gather all text associated with a meme. Then we performed tokenization, lemmatization, and stemming to simplify all of the words. This was done using the NLTK and gensim Python libraries (Rehurek and Sojka 2011 ; Loper and Bird 2002 ). Tokenization is used to split the text into a list of words, make all characters lowercase, and remove punctuation. Words that have fewer than 3 characters and stopwords were removed. Words were lemmatized so that all verbs occur in their first person, present tense form. Finally, words were stemmed, or reduced to their root form. For example, the “processed words” extracted from three memes using OCR, tokenization, lemmatization, and stemming can be seen in Fig. 3 .

Examples for negative, neutral, and positive sentiment memes along with a few example words obtained from OCR. The memes have been collected from Reddit.com

Using the processed text data we can extract some potentially predictive attributes such as sentiment and word count. First, we calculated the sentiment scores that quantify the feeling or tone of the text (Liu and Zhang 2012 ). If the text is positive or happy, it scores closer to 1, and negative or sad texts score closer to 0. Examples for different sentiment scores are shown in Fig.  3 . The sentiment model we used to analyze the processed meme text uses a recurrent neural network known as LSTM (Long short term memory) (Shreyas 2019 ). This network remembers the sequences of past words in order to make predictions about the sentiment of new words. The model was trained on dictionaries with hundreds of thousands of words that were already scored for sentiment.

Figure 4 illustrate the relationship between the extracted text features and the normalized upvotes. The framework in which memes compete for limited user attention suggests that users may respond best to memes with shorter texts. Indeed, we found that the amount of text a viewer is required to read correlates negatively with upvotes. This is in alignment with the findings of Kruizinga-de Vries et al. ( 2012 ) on the popularity of brand posts in the social media.

In Fig. 4 we can also observe that neutral memes perform better than extreme ones, but of the extremes, negative sentiments perform better than positive sentiments. These results contradict previous finding that online news content which evokes high arousal, especially negative, is more viral than neutral content (Berger and Milkman 2012 ). Another paper found that popular memes tend to be unique, in terms of sentiment and other features, whereas memes that are similar to most other memes perform poorly (Coscia 2014 ). It is unlikely that humor is usually helped by neutral charged content, instead its associated with surprise which is related to arousal (Chandrasekaran et al. 2015 ). This result suggests that the jokes in memes particularly are about mundane, not arousing topics.

The relationship between the extracted text features and the normalized upvotes

The words extracted from the text were encoded as numerical attributes and analysed for their relationship with meme content and popularity. Similar groups of words such as “coronavirus”, “virus”, and “pandemic” were grouped together under one name. The 7 word categories can be viewed in Table 2 . Then, these categories, along with the top 28 most frequently occurring words in the processed_words attribute (in Table 1 ), were one hot encoded into 35 numerical feature attributes. In total, including text length, word count, and sentiment scores, there are 38 numerical text features.

A word cloud in Fig. 5 created from every word we gathered indicates certain topics are especially prevalent in the memes from late March, 2020. For instance, “coronavirus”, “toilet paper”, “quarantine”, “work”, “home”, “school”, and “friend” all appear most prominently in the word cloud, though some appear in slightly different versions due to our processing. “Memat” is notably one of the prominent words in the word cloud. A popular meme-making website entitled mematic is used by many Reddit users, and each meme produced from the website contains a mematic watermark to indicate its origin. The watermark was apparently read by the OCR as text from the meme. Hence, “memat” is one of the more prominent texts found among the memes. The largest words in Fig.  5 shows that current events do play a great role in the content of memes, though whether this sort of content has a great effect on popularity is another question. An initial analysis showed than in most cases, the words included in table 2 are just as prevalent in the top 5% viral memes as in non-viral memes. The largest difference we found was for the category COVID-19 synonyms in which 23% of dank memes contained at least one word from the category and 17% of not dank memes contained a word from that category. We aim to answer this question further in the following sections by studying the importance of these features to machine learning models.

Wordcloud generated from all text in our scraped memes

• Image analysis

Most images on the Internet are not neutrally charged. Subtle differences in color, definition or setting can convey vastly different meanings to the viewer. In general unique, bright, high definition images with a low depth of field are ranked more aesthetic by viewers (Datta et al. 2006 ). Additionally, the presence of certain objects in a photo lead to greater or lesser popularity on Flickr (Khosla et al. 2014 ). However, memes often have comedic, relatable or reactionary value which is not necessarily aesthetic. The importance of image features may differ for memes as opposed to other types of Internet images.

The image is an important part of a meme. An initial analysis of thumbnail area in our data showed that the majority of memes had the largest thumbnail size available on Reddit. The more popular memes also tend to have larger thumbnail areas.

In addition to thumbnail area, we looked at the colors present in the most popular meme images. Color and thumbnail area are examples of simple image features, aspects of an image that are easily interpreted by human viewers. The colors that the human vision system perceives as distinct have larger value coordinates in HSV (hue, saturation, value) color space, therefore we extracted colors from the HSV versions of our meme images. We used an OpenCV image segmentation technique (Stone 2018 ) to isolate 30 colors, including a small range around the specific HSV value of the color. This range was used to mask the images, revealing only pixels within that color range. The number of pixels in the mask was normalized for images of differing sizes by dividing by the total number of pixels in the image. These color attributes represent the amount of each of the 30 given colors present in the meme images.

Figure 6 shows the amount of each color attribute in the upper 95 percentile of popular memes. In general, muted colors are more abundant than bright colors in viral memes. Perhaps because memes tend to be mundane photos, often blurry in self-made way, unlike professional photography. This result differs from the similar analysis done by Khosla et al. ( 2014 ) in which reds and colors that are more striking to the eye showed the greatest importance. However our results both present blues and greens as less important. Another paper found that images with animate objects tend to be ranked as more funny than images with inanimate objects (Chandrasekaran et al. 2015 ). Some of the colors found in the most popular memes may be colors that are more common in animate things like animals or human skin and hair tones. Black and off-white were also most present in the bottom 5% of least popular memes, but other parts of the color profile differed. Greens and especially blues were more abundant in these memes, and some shades of orange and brown with large values in Fig. 6 were not present at all in the least popular memes.

Color content of popular memes. The average amount of each color attribute in the top 5% of memes, 3728 records, with the most normalized upvotes. Bars that go below 0 indicate that none of that color was present in the dank memes

In addition to colors, we extracted the average hue, saturation, and value components of the meme images. These are low level image features because while HSV mimics the way human (and now computer) vision works, these components of an image are not always obvious to the viewer. The relationship between these attributes and meme popularity is visualized in Fig. 7 . Hue and saturation show a slight negative correlation with upvotes, indicating that yellow-green hued, less saturated images have a positive impact on popularity. Value shows a slight positive correlation, indicating that images with higher value, more distinct and less dark colors may get more upvotes. These features tended to have significant predictive power in the machine learning models.

Average HSV and normalized upvotes. The relationship between meme popularity, measured by normalized ups, and components of the HSV color space

We also analyzed high level image attributes that aim to describe the semantic meaning present in images. By processing the images with the pre-trained Keras’ VGG-16 neural network, we were able to roughly identify what objects are present in the meme images (Chollet et al. 2015 ). Figure 8 shows the neural net’s meme content predictions, with the associated probability of that prediction. This categorical data is not necessarily accurate, but does convey some level of information about the subject matter of each meme image. Table 3 lists which VGG-identified content was most common in the top 5 percent most popular memes and lower 5 percent least popular memes. These two columns list the top 10 unique values in each of these groups. The most and least popular memes also shared some VGG-identified content, such as the categories website, comic book, and book jacket. This is not surprising as many memes are created using meme-making websites like Mimetic. The top ten shared content categories are listed in the third column of Table 3 . Many of the overlapping categories reflect the formatting of the meme and these were the most common categories identified by the VGG-16 neural network across all of the data records. Because terms about the image formatting were so common, we combined these terms into one category called formatted . The neural net identified specific objects within the images less frequently, but these observations, as shown in Table  3 , did tend to differ between the most and least popular 5 percent of memes.

While much of the VGG-identified content referred to miscellaneous items, some of the top categories related to the growing culture around the COVID-19 pandemic. Along with toilet_tissue, lab_coat and mask were within the top 40 most common VGG-identified components in the whole dataset. Many medical masks such as are worn to prevent the spread of COVID-19 were also misidentified as muzzels, gas masks or neck braces by the neural net. Thus these components were combined under one numerical attribute category, masks .

Neural net high level image features. We extracted high-level, categorical image features from the memes using the pre-trained keras neural network. Examples show the three most certain predicted image components and their probabilities by Keras VGG Neural Net. The memes have been collected from Reddit.com

The categorical VGG-identified data was converted to numerical data in a number of ways. Upon observing that many of the VGG-identified objects belonged to similar categories, such as the meme formatting and masks mentioned before, we grouped these into 9 VGG content categories: animals , formatted , sports , clothes , masks , technology , violent content , food and vehicles . Note that some of the content identified in Image 8 would be encoded in one or more of these categories. The categories were then one-hot-encoded into numerical features columns along with the next 8 most common VGG-identified content. These features were somewhat sparse, as the binary one-hot-encoding indicated whether or not a certain vgg prediction, or category, was found in the top three vgg content predictions for the meme. In addition to the binary features, we included the probabilities associated with the top 3 vgg content predictions for an additional 3 vgg related features. These probabilities tended to be ranked as important to the machine learning models discussed in the nextt section.

After these alterations to the raw image data, there were a total of 53 numerical image attributes. The abundance of features leaves room for fine-tuning and eliminating some of them to improve the models. Here, we suggested that certain colors and objects may be associated with viral memes, but the machine learning models will provide more clarity as to what characteristics are actually influential in determining the popularity of a meme.

Gradient boosting and random forest

We selected Gradient Boosting and Random Forest models to perform the binary classification task of placing a memes in the dank or not_dank categories. Both models are ensemble learners that benefit from the accumulated results of weak-learners. The models are trained and tested using the full array of data attributes listed in Table 1 , and discussed in the image and text analysis sections. They make predictions based on the same set of labels in which viral memes in the top 5% of normalized upvotes are considered dank , labeled 1, and the rest are not_dank , labeled 0. By observing how these ensemble models make their predictions we can garner insights about the most important features that make memes go viral. Using two models for this task will further validate our results.

Gradient boosting is an ensemble method of weak learners with the optimization of a loss function (Natekin and Knoll 2013 ). Boosting models fit a new learner on the observations that the previous learner could not handle. The model serves as a good classifier for rank, which suited our binary classification task. The gradient boosting classifier of sklearn’s ensemble package builds in a forward stage-wise manner, which means that a user-defined number of regression trees are fitted on the negative gradient of either the binomial or multi-nominal deviance loss function at each stage and the weighted sum of the learners will be the output (Pedregosa et al. 2011 ).

The Random Forest is an ensemble method made up of many decision trees. The success of the ensemble depends on the strength of the individual trees and the level of dependence between them. This model is a good choice for our data set because it performs well with a mix of categorical and continuous features, it can handle many features and large amounts of data without risk of over-fitting, and the tree structure is easily interpreted (Breiman 2001 ). It is quite similar to the Gradient Boosting model, meaning they can be easily compared, and the differences between the models serve to reinforce our results, as our findings are replicated by two models.

Performance and features importance

A limitation to the Random Forest and Gradient Boosting ensemble classifiers is that in their original form they do not perform that well with unbalanced data (Brownlee 2020 ; Liu et al. 2017 ). However, many methods for learning unbalanced data with these ensembles have been developed (Chen and Breiman 2004 ). We modified the models to reduce the effect of skewed data, and generally improve the prediction results. Firstly, we used the BalancedRandomForestClassifier from imblearn as our Random Forest model. This classifier uses random undersampling to train on more balanced subsets of data by resampling data from the training set for each tree classifier in the ensemble. The distribution of positive and negative labels in the training sets can by controlled by the parameter sampling_strategy which represents the proportion of majority to minority class labels. Both the Random Forest and the Gradient Boosting models used 5-fold cross validation, the class weight parameter, and GridSearchCV from sklearn to fine-tune the classifiers’ parameters.

Following these modifications, we split the data into a 53,843 record training set and 26,520 record test set, a 67–33% split. Both models predicted labels on the test set with an AUC of around 0.7 as shown in Fig. 9 . Accuracy, recall, precision, and F-1 scores for the highest performing (Random Forest) model can been seen in Table 4 , and scores for the gradient boosting model were quite similar. Both models performed poorly in precision. Consistently, the models predicted a larger proportion of positive labels than was realistic for the data set despite the measures we took. Some of the measures we took to to counteract this effect, such as re-assigning thresholds, were adjustable at a cost. Increasing the probability which was sufficient for a positive label would improve the model’s precision but adjusting too much led the recall and accuracy scores to decrease.

The difficulty of predicting the imbalanced data, indicated by low precision scores, may be due to the lack of social network features. Perhaps while content-based features can predict whether a meme has a chance at going viral (has merit), social network features are what determines which of those memes actually do go viral. This supports Barabási’s theory on success in general in which merit is the first step to becoming successful, but social networks determine who among those with merit becomes a superstar (Yucesoy and Barabási 2016 ).

In addition to the modifications listen above, we tried a few undersampling methods. We performed a 67–33% train-test split for all models. The undersampling results for the best performing models, the Random Forest, are listed in Table 4 and the results for the gradient boosting model were very similar. Using the random undersampler module from sklearn, we undersampled only the training data. This did not have a large effect on the models’ performance, indicating that the other measures we took to counteract the imbalanced dataset, and generally improve results, were effective. We also tried undersampling both the test and train data, this improved the precision, and consequently F-1 scores immensely but had only a small effect on our AUC. (Of course, changing the distribution of the test set alters the nature of our prediction goals, therefore we do not report on the results of these tests extensively). We also note that while the precision value might look quite small without adjusting for the unbalanced distribution, but it means a more than 70% improvement to random guessing dank memes.

ROC curve and features importance of gradient boosting and random forest models. a The ROC curves of the models without undersampling techniques. b Features importance for both models

The features importance plot in Fig. 9 shows the relative importance of the data features from Table 1 for the Gradient Boosting and Random Forest models trained without undersampling. The two models showed similar features importance, with some variability. Additionally, many of the points explored in earlier sections about the features’ relation to upvotes are reinforced by the importance scores. Simple features such as text length and image size ( thumbnail.height ) showed great importance for predicting viral memes. The important colors in Fig. 9 also align with the most abundant colors in Fig. 6 . Gray, off-white, and pure-black are some of the most important colors for the model and are most abundant in viral memes. Figure 9 also indicates that overall more image-based than text-based features are important. However, this could be due to the fact that we included more image based than text based features overall, 53 as opposed to 38.

Incremental predictive power of image and text features

In addition to the most important features shown in Fig.  9 , we investigated whether image or text features have more predictive power for determining viral memes. We used the Gradient Boosting and Random Forest models discussed previously with the full amount of train and test data. Differing from the earlier analysis, we trained four Gradient Boosting and four Random Forest models, each of the four with different subsets of features. The models are trained with image-only attributes, text-only attributes, both, and all attributes from Table 1 to show the incremental predictive benefit of these feature groups. The viral nature of memes makes predicting high performing memes more difficult, but since the skew is an inherent part of the data we decided against undersampling the data for this part of the analysis as changing the distribution alters the nature of our prediction question.

Incremental importance of image and text based features. a Random Forest model and b Gradient Boosting model

As for the previous models presented in Fig. 9 , the models were trained with a set of 53,843 and test set of 26,520 data records, a 67–33% split. All of the modifications and fine-tuning, including class-weight and GridSearchCV, efforts used in those models are the same here. The exact feature description differs slightly between versions of these models due to fine-tuning efforts in which certain colors or processed words may have been eliminated if they showed no importance to the model. These slight differences did not disrupt the organization in which the four models had either only text related features, only image related features, both or all features including social network features scraped from the Reddit metadata such as subscribers.

Figure 10 shows the results of the incremental predictive ability analysis. Not surprisingly, the model trained with all data outperformed the other models. This aligns with previous results in which text and network data held more predictive power for image popularity on Flickr (Khosla et al. 2014 ). It is impressive that adding only four network features ( subscribers , created_utc , is_nsfw , and time_of_day ) increased the AUC by 0.02 for the Random Forest Model. Given the results that social network features have shown in predicting meme popularity in past papers (Weng et al. 2012 , 2014 ), it is likely we would have seen a much greater increase in AUC if we had included other social network features, too. Surprisingly, it is not obvious whether image related or textual attributes have the stronger predictive power since the Random forest model performed better with the image related attributes, while the Gradient Boosting model performed better with textual attributes. However, it is clear that they both have incremental predictive power over each other in both models.

Transfer learning with convolutional neural network

Convolutional neural network

Convolutional neural network (CNN) is a class of artificial neural networks that has gathered attention in recent years due to its versatility and ability to achieve excellent performance in a multitude of problems. Among others, it had been used by computational linguistics to model sentences’ semantics (Kalchbrenner et al. 2014 ), by radiologists to segment organs (Yamashita et al. 2018 ), by ophthalmologists to identify diabetic retinopathy in patients (Gulshan et al. 2016 ). CNN’s success lies in its architecture that allows it to learn inherent spatial hierarchies from its training data through recognizing and learning low-level patterns that build up to high-level patterns (Yamashita et al. 2018 ). This ability to extract important features means that the CNN is able to identify different levels of image representation and capture the relevant ones in the training data, making this model family especially suitable for computer vision tasks (Jogin et al. 2018 ). Past research has shown that CNN is also able to perform well when it comes to identify an image’s popularity (Khosla et al. 2014 ). Following this vein of research, in this section, we examine whether we could classify a meme’s dankness solely based on raw image data, ignoring the attributes that we used in previous sections.

Sampling the dataset

The dataset contained approximately 76,000 downloadable images. Because of the imbalanced distribution in posts’ upvotes as can be seen in Fig. 2 , we chose to make the not_dank class to be the same size as the dank class by randomly sampling from the 70,000+ images in the not_dank class. We then divided this sub-dataset into training set, validation set, and test set in the following ratio: 50%, 25%, 25%. The exact number of images used in each set is shown in Table 5 .

Transfer learning

Deep CNNs normally require a larger amount of training data than we had. Previous research has shown that in cases where there is limited training data, transfer learning is an effective method to significantly improve the performance of the neural network (Tammina 2019 ) as well as reduce overfitting (Han et al. 2018 ). Several transfer learning methods have been proposed throughout the years. Here, we adopt the method proposed by Yosinski et al. ( 2014 ): using the top layers of the pre-trained CNNs as feature extractors, then fine-tuning the bottom layers with our own dataset, and adding a set of fully connected layers for prediction. The main reason we used this approach is the domain difference between our dataset and the ImageNet dataset which makes it necessary to retrain some of the last layers.

The pre-trained CNN models that serve as our feature extractors were trained using data from the ImageNet Large Scale Visual Recognition Challenge (ILSVRC) (Russakovsky et al. 2015 ). This dataset consists of roughly 1.2 million training images, 50,000 validation images, and 150,000 testing images in 1000 categories (Krizhevsky et al. 2017 ). The pre-trained CNN models we picked—namely, InceptionV3, VGG16, ResNet, Xception, MobileNet—are top performers in previous ILSVRC competitions, and their weights trained with this dataset are all available in Keras (Chollet 2015 ). Out of these models, VGG16, InceptionV3, and Xception proved to be the best performing feature extractors for our dataset. For further information about the models see Table 6 . We will provide more details about how we fine-tuned each of these neural networks in a later section.

Image data augmentation

Data augmentation is used to expand the dataset by generating and including similar yet slightly modified entries in the training process. In regard to image recognition tasks, the most traditional methods are to add noise or to apply affine transformations (e.g. translation, zoom, rotation, mirror, flip) (Suk and Flusser 2003 ). Previous research has shown that this procedure could reduce error rate, helps with overfitting, and allows the model to converge faster (van Dyk and Meng 2001 ). Yosinski et al. ( 2015 ) has reported that after augmenting the dataset with randomly translated images, their model see a decrease in error rate from 28 to 20%. Another example is in the design of the VGG16 neural network that was among the winners of the ILSVRC 2014 competition, Simonyan and Zisserman also employed image augmentation techniques such as flipping the images, including randomly cropped patches of the images, or changing color intensity (Simonyan and Zisserman 2014 ). The authors claimed that this data augmentation helped decreased the error rate by 1%. Similarly, our best three models are all trained using a dataset augmented with the following Keras ImageGenerator transformations:

Rescale the pixel values (between 0 and 255) to the [0, 1] interval.

Zoom into the image randomly by a factor of 0.3.

Rotate the image randomly by 50 degrees.

Translate the image horizontally randomly by a ratio of 0.2 factor the image width.

Translate the image vertically randomly by a ratio of 0.2 factor the image height.

Shear the image randomly.

Flip the image horizontally randomly.

Fine-tuning strategies

Since each network has different architectures, we needed to employ different fine-tuning strategies to each of them. The fine-tuning strategies we used are listed below:

For VGG16, freezing the first three convolution blocks, fine-tuning the weights of all the other layers (in the two other convolution blocks in the network, plus the last three fully-connected layers).

For Xception, freezing the weights of all convolutional layers, and fine-tuning the weights of only the last three fully-connected layers.

For InceptionV3, freezing the weights of all the layers up until the “mixed7” layer, then fine-tuning the rest of the layers in the InceptionV3 network plus the last three manually-defined fully-connected layers.

For all networks, dropout is implemented after the first and the second layer of the last three fully-connected layers.

For all networks (VGG16, Xception, InceptionV3), the last “softmax” layer is removed, and replaced by a “sigmoid” layer for prediction.

The images are resized to fit the default input size for each of the network (299x299 for Xception and InceptionV3, 224x224 for VGG16).

All networks include ReduceLROnPlateau functionality from Keras that reduces the current learning rate by 25% whenever the validation accuracy does not increase in the span of 3 epochs.

All of the neural networks tested for this research were evaluated on the test set using several metrics (Accuracy, Precision, Recall, and F-1 Score). The results are recorded in Table 7 . We also calculated the ROC curve of the best 3 models along with their AUC scores which are shown in Fig.  11 a. Figure 11 b, c show the change in the training and validation accuracy and loss during fine-tuning the VGG16-based model, which produced the best AUC score.

ROC curves of the 3 best CNN models and the training curves of the best model. ROC curves and AUC scores a of the best models based on pre-trained CNN models. The accuracy ( b ) and loss ( c ) during training of the best VGG16-based model

From Table 7 and Fig.  11 , we can conclude that the VGG16-based model seems to slightly outperform the other models, while the Xception-based model comes in second, and the InceptionV3-based model in third place. We can also conclude that the best neural network (AUC = 0.63) performs equally with the best performing ensemlbe model trained on hand-crafted image features (AUC = 0.63).

A confusion matrix with example memes according to the CNN model. The green bordered parts show True Positive and True Negative instances where the model prediction is the same as the real target label. The red-bordered parts are False Positive and False Negative instances where the predicted and true class labels do not match. The memes have been collected from Reddit.com

From our experiments with different models, we have observed that using image augmentation helps with making the models converge faster and achieve a higher accuracy. Fine-tuning the last few layers of the CNN models with the transfer learning methodology also improved the performance of our models. The over-fitting issues we encountered were depressed by adding a dropout rate between layers and reducing the learning rate between epochs. Although we have experimented with several models and parameters, the model performances show that it is hard to predict the dankness of image-and-text memes using the image content alone. This finding is in line with similar previous research where image-content has smaller significant compared to social contexts and other features for predicting image popularity on Flickr (Khosla et al. 2014 ). The difficulty of content based popularity prediction of memes is also illustrated by the memes where the model prediction does not match the true class label (see Fig.  12 ). It is a difficult task to tell the true class of these memes both for humans and machines.

In this paper, we analyzed image-with-text memes collected from Reddit. Using machine learning models we investigated whether viral memes can be predicted based on their content alone. We considered the problem as a binary classification task defining viral memes as the top 5% of all posts in terms of upvotes. Our best performing model is a random forest model that performs moderately well with an AUC of 0.6804, accuracy of 0.6638, precision of 0.0854, recall of 0.5897. While the precision value might seem quite low at first sight, it is a 70% improvement to random guessing dank memes.

Moreover, we studied the most important features and we found that gray content, image size, saturation, and text length have the greatest impact on the prediction. While there was a lot of COVID-19 related content in the dataset overall, visible in the word cloud, and some vgg-identified image content, features related to COVID-19 proved less important to the performance of the models. Thus, we estimate that while memes often reflect pressing world issues, the presence of this sort of content has little impact on whether memes will go viral. We also investigated the predictive and incremental predictive power of image and text features. While we cannot conclude whether image related or textual attributes are the stronger predictors of a meme’s success, we have shown that they both have incremental predictive power over each other. If we use only the images as an input with a convolutional neural network we can reach AUC = 0.63, and that agrees with the performance of the best performing random forest model trained on hand-crafted image features. Comparing our results with other works where social network and community features were also used for predicting popularity (Weng et al. 2012 , 2014 ), we can conclude that while the content-based analysis can also predict success with reasonable efficiency, social network features could improve the performance significantly. While content based features could predict memes with merit, social network features determine which among those with merit actually go viral.

It is also fair to acknowledge some limitations of this study. Due to the the short time period in which we collected data—in the intense moment at the beginning of the coronavirus outbreak—our results cannot necessarily be universally generalized. However, we believe that many of our findings are relevant for meme popularity in general. Moreover, the short time period of the collected data did not allow us to study the temporal and dynamic aspects of meme success or identify so-called “sleeping beauties”. The latter is a phenomenon of information spread in which a meme will remain unnoticed for a long period and then suddenly spike in popularity long after it was originally posted (Zhang et al. 2016 ). We propose these aspects of meme popularity prediction for future research. Furthermore, an other stream of relevant future research would be to analyze memes inspired by COVID-19 alone.

Availability of data and materials

The datasets analysed during the current study are available in the GitHub repository: https://www.github.com/dimaTrinh/dank_data .

Abbreviations

Hue saturation, value

Optical character recognition

Long short term memory

Receiver operating characteristic

Area under the curve

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Original research article, internet memes: leaflet propaganda of the digital age.

• University of Maryland Global Campus, Adelphi, MD, United States

Internet memes are one of the latest evolutions of “leaflet” propaganda and an effective tool in the arsenal of digital persuasion. In the past such items were dropped from planes, now they find their way into social media across multiple platforms and their territory is global. Internet memes can be used to target specific groups to help build and solidify tribal bonds. Due to the ease of creation, and their ability to constantly reaffirm axiomatic tribal ideas, they have become an adroit tool allowing for mass influence across international borders. This text explores the link between internet memes and their ability to “hack” the attention of anyone connected to internet using dense modality and cognitive biases. Furthermore, the text discusses Internet meme's ability sew discord by consistently reaffirming preexisting tribal bonds and their relation to traditional PSYOP tactics initially used for analog leaflet propaganda.

Methodology

Through the use of media archeology this article aims to illuminate the evolution of analog leaflet propaganda into its contemporary digital form of internet memes. Through the use of macroscopic comparison and microscopic analysis a trend of parallel persuasion techniques can be observed between analog leaflet propaganda and internet memes.

Introduction

This article focuses on analog leaflet propaganda and modern digital internet memes in regards to their composition, dissemination, and application among their respective target audiences. Through the use of macroscopic comparisons a trend of parallel persuasion techniques can be observed between analog leaflet propaganda and internet memes. The article further highlights the parallel uses of both mediums in relation to their ability to utilize psychological tactics to disseminate information on a macroscopic level while simultaneously targeting a microscopic audience. Currently, aerial leaflet propaganda and internet memes are both in use in their respective theaters (the real-world and the digital-world). The use of aerial leaflet propaganda historically and the parallel usage of aerial leaflet propaganda and digital memes contemporarily offers a unique opportunity to explore their previously overlooked entanglements. Through excavating historical uses of aerial leaflet propaganda and their respective PSYOP tactics a more comprehensive analysis of internet memes and their role in digital manipulation becomes possible. This article is meant as a theoretical analysis of internet memes, and their propagandist properties, so that other researchers may bring forth empirical examples. The article follows a road map beginning with the historical aerial leaflet propaganda tactics, strategies, and goals highlighting the importance of targeted audiences. The focus of the article then shifts to a microscopic view of what internet memes are, and their innate faculties that allow for enhanced malleability and dispersal (including heuristic properties). The final portions of this article shine a spotlight on internet memes at work in the real world and future research opportunities stemming from this body of research.

Thought Bombs Raining Down From Above

Targeted audiences and strategically targeted objectives have been the foundation for which effective propaganda based information dissemination has developed. Every mass propaganda campaign needs a mechanism of conveyance to reach its target audience. For over a century engines have thundered across the skies around the globe with the sole purpose of being the mechanism of conveyance for propaganda based information dissemination. Leaflet propaganda is traditionally, “disseminated by hand, trash bag, leaflet box, and leaflet bomb, depending on the aircraft type and tactical situation” ( US Army, 2003 , k-10). In advance of the United States (hereafter US) led World War II invasion of Okinawa, Japan (1945) about six million aerial leaflets were dropped ( Schmulowitz and Luckmann, 1945 , p. 485). During the US's involvement in the Korean War (1950–53) US and United Nations forces scattered ~2.5 billion leaflets (over two million leaflets a day) on their targeted audiences, the Chinese forces, North Korean forces, and civilians ( Kim and Haley, 2018 ). Each piece of paper was a key hoping to unlock a new way of viewing the conflicts at hand; As Schmulowitz and Luckman wrote, the aerial leaflets were essentially “thought bombs” ( Schmulowitz and Luckmann, 1945 , p. 428). These leaflets came in curious forms some of which were humorous, some informative, and others downright terrifying. Before moving onto how these same principles have evolved into their modern digital iteration it is best to take a macroscopic jaunt through the PSYOP driven tactics and strategies of analog leaflet propaganda in isolation before zooming in and intertwining them with their latest digitally driven iterations (internet memes) for a clearer picture of their parallel properties. The following example focuses on the aforementioned Okinawan and Korean conflicts. These were chosen among many other examples due to the depth of mass propaganda-focused scholarship available and the strict modal and cultural limitations of the propaganda in play in each theater (a significant point highlighted later in this article).

In both the Okinawan and Korean conflicts aerial leaflet propaganda focused on two categories of dissemination (target audiences): Those that were tactical and those that were strategic ( Schmulowitz and Luckmann, 1945 , p. 428). According to the work of Schmulowitz and Luckmann (1945 , p. 428), the tactical target audience was primarily geared toward lowering the morale of enemy combatants often via delegitimization of their leaders, cause, or tactical situation. In conjunction with the tactical target audience leaflet propaganda would simultaneously bombard the Strategic target audience comprised of civilians: the goal being to persuade them into acting in ways helpful (directly and indirectly) to the allied military operations (p. 428). Propaganda would rain down in the forms of posters (similar to the macro-image memes discussed later), newspapers (Ryukyu Shuho/Rakkasan News), comics, and photos among others ( Schmulowitz and Luckmann, 1945 , p. 429). The same audiences were targeted in the Korean War with, “millions of messages directed at friend and foe” in which both civilians and enemy combatants were targeted with specific goals in mind ( Psychological Warfare in Korea, 1951 , p. 65–67; Kim and Haley, 2018 ). The propaganda distinguished between each category of specific targeting hoping to alter the thoughts and actions of the targeted audiences. The persuasive tactics fit broadly into four key areas of targeting.

The four key areas exploited to attempt to persuade their target audiences were as follows: ideology appeal, personal gratification appeal, communal values-focused appeal, and information dissemination ( Kim and Haley, 2018 ). The four categories of persuasion created boundaries and allowed propagandists to generate tailor-made propaganda for their target audiences. The importance of using rhetoric and visual modalities to reach tribal based targeted audiences is vital to the success of such propaganda operations. In the Okinawa theater these categories set targeted intentionality over broad range of connected ideas through crediting or discrediting military and social figures. For example, the emperor, military cliques, the Yamato spirit, Japanese military leadership, the burden of civilians, among others were selected as key targets in [de]legitimizing the role of both state actors ( Schmulowitz and Luckmann, 1945 , p. 485–487). After careful study of the target audiences the US propagandists generated 32 audience specific archetypes in which to create propaganda and to reframe the US and allied forces as a savior against (what was framed as) the militaristic tyranny of Japan ( Schmulowitz and Luckmann, 1945 , p. 485–491). The same strategy was deployed in the Korean War, albeit with slightly differing attributes to their targeted audiences ( Psychological Warfare in Korea, 1951 ; PsyWar Leaflet Archive - 141-J-1, 2012 ). In both theaters real-world action was taken due to creation and dissemination of information via aerial leaflet propaganda ( Schmulowitz and Luckmann, 1945 ; Psychological Warfare in Korea, 1951 ; Kim and Haley, 2018 ). The “thought bombs” were able to target audiences, use rhetoric and modalities that resonated with the target audiences, and utilize heuristics implicit in their respective rhetoric to call to action various tribal groups in a wartime theater. Today the leaflets are still dropped over enemy territories, with the same four points of focus and categories of dissemination, but leaflet propaganda has evolved and the range of airplanes and cost of production of such analog methods are no longer limited by the physical realm of dissemination.

Now their only limitations are Internet access and that of the imagination. Internet memes (colloquially described simply as memes) are one of the latest evolutions of leaflet propaganda and an effective tool in the arsenal of digital persuasion. Internet memes' ability to utilize dense modality and cognitive biases allows them to help sew discord by consistently reaffirming preexisting tribal bonds. As the macroscopic look at aerial leaflet propaganda comes to a close the next pertinent questions arise: what exactly are internet memes and how do they parallel the strategies and tactics of aerial leaflet propaganda?

Memes and their Distribution

Unless one abstains from Internet and social media use internet memes will indubitably be something one has come across. They pervade Facebook timelines, creep into Instagram posts, serenade the Twitterverse, make the nightly news, and have become a staple of digitally based communication. According to Statista.com Facebook alone had an active user base of 2.5 billion people in the final quarter of 2019 ( Clement, 2020b ). Instagram and Twitter came in second and third, respectively, both boasting over 1 billion active users ( Clement, 2020c ). Of these 74% of Facebook users and 42% of Twitter users visit daily ( Pew Research Center, 2019 ). These numbers are global users, displaying the awe-inspiring power of the Internet in its ability to connect people across the world. Furthermore, 35% of Gen Z and Millennial aged users of social media are statistically “very likely” to share other people's memes ( Clement, 2020a ). With such high numbers of people using social media it follows that memes would be a likely tool of idea dissemination.

The unique nature of internet memes alters this dynamic allowing for streamlined access to the broadcasting capabilities of the Internet (particularly social media outlets) to disseminate ideas to a wide audience. Ross and Rivers referring to the ideas of Wiggins and Bowers, describe internet memes as, “artifacts of participatory digital culture” aptly describing their functional use (as cited by Ross and Rivers, 2017 , p. 1). Their ability to be created, used, disseminated, and remixed by anyone with Internet access opens doors to previously unfounded participation in regards to both societal and political issues ( Anderson and Lee, 2020 ). In essence, each computer, smartphone, or tablet becomes a readily available tool of conveyance; distributing ideas that could potentially spread across the globe. In fact, memes have such promise in the realm of propaganda and information dissemination that the Defense Department and DARPA have studied their abilities to influence culture, reinforce ideology, and even alter behavior ( DiResta et al., 2019 , p. 50).

Although seemingly an empowering tool for the individual they can still function in the same manner as their analog forbearers, as a mechanism of the larger State entities and the reigning ideologies within it. Internet memes' success and failures are highly dependent upon the cultural and linguistic limits of their targeted audience. They are a product generally created for a specific [sub]culture. Although their tactics and traits have been revised for a digital medium, their entanglements with traditional methods of State sponsored psychological operations (PSYOPs) are strikingly similar. Regardless of the position or statement of a given meme its success is still bound by the cultural discussions and norms within which it is shared: a trait shared by its analog forbearers. To truly begin to understand the power of the meme its etymology and modal properties must first be explored.

Despite the popularity of internet memes their etymology often escapes the average Internet user. The word “meme” can trace its etymology to Greek “ mimēsis ” relating to the way in which art imitates life ( Mimesis, 2020 ). One of the most well-known excerpts of mimesis can be found in Plato's Republic , noting how a painter may know how to represent an object, but may not know how to use one in reality. Plato writes, “An image-maker, a representer, understands only appearance, while reality is beyond him” ( Plato, 2010 375 B.C.E, 70). Plato may turn out to have an apt divination for life in the Digital Age. Mimesis has a long history of study, though it was not until more contemporary times that it was attributed to social constructs and their dispersal into a given culture.

Contemporary internet memes can trace their lineage to Richard Dawkins' descriptions of memes in his seminal work, The Selfish Gene (1976). To paraphrase Dawkins' idea, memes are small bits of culture that act as if they were individual genes within the field of biology. Each artifact carries with it a piece of the culture in which it was created. To continue with the metaphor, these genes then combine to become parts of a larger genome (the larger social-consciousness) ( Dawkins, 1976 ). In order for the gene to function within the genome it must have DNA that can be read and understood by it. Internet memes must also be able to be read and understood by their target audience to have an effect. Ross and Rivers contend that it is not only the language that matters, but also the culture, worldviews, emotions, and feelings of the audience that propels them into the broader social consciousness ( Ross and Rivers, 2017 , p. 2). Returning to the metaphor, these keys factors are essential ingredients that make up the nucleotides of the DNA. All of these pieces are found to be combined in internet memes, allowing them the possibility of viral power in a given culture. With the essential, yet unseen, inner workings of the internet meme in place it is the easily observable aspects that will be discussed next.

Internet memes occur in a wide range of medias but generally take the form of animations, GIFs, videos (including those found on Reddit, TikTok, Instagram, Facebook, and YouTube), images, and image macros. Though all of these forms are relevant for the current article, image macros will be the focus due to their ease of creation, transmission, and adaptability as well as their comparability to traditional aerial leaflet propaganda. Due to the ceaseless creation of memes created daily no exact number of internet memes in circulation at a given time is possible. With this in mind according to one of the most popular internet meme sites, knowyourmeme.com , there are currently 3,347 confirmed archetypes/genres of image macro memes officially listed between 2003 and 2020 ( Confirmed Entries, 2020 ). Although image macros have been highlighted here as an example other meme modalities also utilize the techniques of PYSOP driven propaganda and leaflet propaganda.

In a nutshell, internet memes using the image macro form of transmission use a static image and superimposed text. Much like the aerial propaganda dropped from planes (or handed out) both the image[s] and the text play a role in the understanding of the meme. The image relates directly to the given archetype (or genre) of the meme creating a basis for which to understand the meme. Images can relate to a wide range of expression including sarcasm, irony, humor, or advice. This “base” allows for a tacit understanding of the meme on a macroscopic level. For example, the widely known “Condescending Wonka” meme has been in circulation since 2011 ( Condescending Wonka/Creepy Wonka Image #233,240, 2012 ) (see Figure 1 ). This meme features the image of Gene Wilder from the 1971 film Willy Wonka & the Chocolate Factory . The image itself lets the meme consumer know this specific meme will discuss some topic of an ironic nature in which the rhetorical act of condescension is applied for humorous effect. The construction of these cultural artifacts adheres to Semiotic understandings of language. Swiss linguist Ferdinand de Saussure, in their work Course in General linguistics , describes language in terms of signs, signifiers, and signified ( Sassure, 2010 ). The power of signs has been utilized throughout the written record to bond people together under one image and idea. Internet memes harness the power of signs acculturating and reconfirming ideas of how the world really is. One of the cornerstones of the internet meme's power lies within its dense amorphous modality.

Figure 1 . An example of the Condescending Wonka Meme.

Internet memes utilize these functions to create a dense modality, allowing those experiencing memes to, at a glance, comprehend the general context (sarcasm, humor, etc.) from the static image and gain further information. The memes can then become particularly nuanced for the target culture, from the superimposed text. When the memes subscribe to the archetype conventions the signs and signifiers work in conjunction to create a hyper-modality around the signified idea. This modality falls into categories understood by the users and creators of internet memes. Using the basic archetype (i.e., the static image behind the superimposed text) of the meme generates options for nearly infinite amounts of remixing, allowing them to stay current regardless of the idea presented: As long as the meme smith adheres to the mutually understood pre-existing signifier of the internet meme. Although thousands of meme archetypes exist they can be broken down by their purpose into five umbrella categories.

Mickael Benaim, citing the work of Knobel and Lankshear formulated a list of five meme types which are as follows: “collaborative, absurdist humor in multimedia forms; hoax memes; celebrations of the absurd or unusual; and social commentary (social critiques, political comments, social activist)” (as cited in Benaim, 2018 , p. 901). With such a broad array of types internet memes are able to find an audience in lead and sub cultures across the globe. The Internet is rife with millions of examples of each of these categories. The specific topics addressed range from popular culture, politics, to subcultures such as internet memes in Latin and Klingon. Each meme archetype/genre must refer to preexisting sociocultural constructs in order to be successful (in terms of being understood and shared). Memes in their final forms (the static image and the superimposed text) can also, though not always, be restricted by their linguistic and cultural capacities. Although potentially empowering internet memes are not without further limitations in regards to the roles they play in today's technologically savvy world. It should be noted that although humor is quite often the mode of conveyance the subject matter may be deadly serious. Internet memes harness a different mechanism for dispersal than aerial leaflet propaganda, yet both share similar spatial limitations dependent upon their targeted audiences.

One example of such a limitation, relating to ineffective audience targeting, played out in the real world can be found in a New York Times article, “German's Cross Signals in Propaganda Leaflets” ( Associated Press, 1945 ) German leaflet propaganda meant for the eastern front was accidently shot toward the American held western front. The Russian language propaganda aimed at inciting rage against the American forces in the Pacific. Several minutes later the American front received the correct batch, in English, claiming, “Premier Stalin was seeking to destroy America and Britain” ( Associated Press, 1945 ). This unintentional misfire destroyed the leaflet propaganda's ability to disseminate its intended message and displaying the cultural/linguistic range of the propaganda. It is not only the language and the message that must resonate with target audiences, but also the phrasing and cultural sensibilities implicit in the act.

In both theaters discussed in section Thought Bombs Raining Down From Above, propagandists had to frame their language in ways that were culturally acceptable for their audiences. On striking example is the use of the statement “Cease Resistance” instead of “surrender” or “give up” (see Figure 2 ). In order to maintain the appearance of honor and a “shameless” exit from the war in the face of defeat, leaflet propaganda focused on using the statement “to cease resistance” to pander to the target audience's sensibilities ( Schmulowitz and Luckmann, 1945 ; Kim and Haley, 2018 ). This change was made after finding previous messages to not resonate with their target audiences and even backfire into increasing enemy morale ( Schmulowitz and Luckmann, 1945 ). Therefore, careful experimentation, hand tailored messages, and thoughtful audience targeting play vital roles in the art of aerial leaflet propaganda dispersal. Internet memes also have similar limitations imposed upon them particularly relating to their timing, culturally targeted audience, and dispersal range.

Figure 2 . Jesus- We can beat it together (2016) .

As theoretical comparative example, a meme shared in Japanese may not linguistically or culturally be successful with a North American audience and vice versa; although the same genre of meme may be used to infer the underlying meaning of the internet meme. Therefore, internet memes do have limitations correlating to their intended audience and their knowledge of the meme, or what it references within the social sphere, in order to work ( Bradshaw and Howard, 2018 ). Much like dropping Spanish language aerial propaganda on a country such as Djibouti would prove ineffective it is the intended audience (and by extension their demographics, sensibilities, and tribal bonds) that creates the boundaries for the success or failure of an internet meme to become used and shared on a grander scale; much like the targeting of wartime audiences discussed in section Thought Bombs Raining Down From Above.

Furthermore, internet memes can be limited by addition of the (often non-sensical) humorous nature they convey. If they fail to uphold the given standard of their target audience or secondary audiences, and the inherent boundary markers of that culture, they will fail in propagating themselves further than the first initial recipients. Conventional PSYOPs follow similar guidelines when generating propaganda in foreign theaters. According to the declassified 2003 U.S. Army's “Psychological Operations Tactics, Techniques, and Procedures” field manual, generated materials must be, “compatible with the way foreign populations [and by extension target audiences] are accustomed to receiving information” (1–3). Therefore, the modality must match the expectations of the target audiences ( Bradshaw and Howard, 2018 ).

In order for memes or leaflet propaganda to be successful it must capitalize on the timeliness of the event they are referencing ( Coscia, 2018 , p. 70). If a meme references an event too far outside of the social consciousness it is unlikely to take on a viral form. An apt comparison would be dropping World War 2 propaganda leaflets over modern day cartel held regions of Mexico. The message is simply not going to be effective and therefore its virility is squashed from the onset. The creation of effective memes follows the tides of contemporary events; often mirroring the 24-h news cycle from which many internet memes draw their cultural references. Those that target their audience well and craft the meme's narrative in a way that resonates ride the wave, while those that don't drown and sink into the inky blackness of the forgotten places of the world wide web.

Furthermore, if a meme is to be successful in their dispersion, it must not be too similar to other viral internet memes sharing the same information or they will likely face lower success of propagation. As Michelle Coscia, referring to their study conducted on the social bookmarking sites Reddit and Hacker News , writes, “high canonicity lowers the overall success of viral posts at the same time it helps non-viral posts be appreciated” ( Coscia, 2018 , p. 72). By saturating the meme market with similar memes those with novel approaches become more successful. Leaflet propaganda also adheres to similar dispersal boundaries. Kim and Haley (2018) discussing the strategies of leaflet propaganda in the Korean War note, “…each side copied the other's themes and content as counter-propaganda, the themes of the leaflets with an ideological appeal were somewhat similar in that they criticized the societal system of the opponent.” The remixes needed to be similar enough to act as counter-propaganda if they were to be effective tools of manipulation, but not exact copies. If an internet meme is to survive and thrive it must not be an exact clone; much like the genes behind its namesake it must evolve and mutate to survive. This not only maintains the meme genre, but also regenerates interest in the initial samplings. Through the use of remixing the original referenced artifacts become the raw materials with which to remix.

Another essential key to a memes success is its ability to remix cultural artifacts as materials to generate new meaning. Objections to the use of remix to create bona fide meaning from the references among audiences are addressed in Lawrence Lessig's groundbreaking work Remix . He writes, “Their meaning comes not from the content of what they say; it comes from the reference, which is expressible only if it is the original that gets used. Images or sounds collected from real-world examples become ‘paint on a palette'” ( Lessig, 2009 , p. 74). Each event that strikes a chord with a culture or subculture has the potential to add to the modality of a meme and its remixes; particularly in regards to pop-culture artifacts. This not only increases “fun” of recognizing the cultural references in a meme, but also, potentially increases its resonance with non-targeted audiences as well: further aiding in the internet memes potential for broader dispersal. In short, internet memes remix cultural artifacts to generate new meanings by leveraging the power of other cultural references for increased audience participation and dispersion ( Lessig, 2009 , p. 76). Therefore, an adequate sense of cultural understanding (by both meme creators and meme consumers) plays a large role in the success or failure of a meme.

The mimetic nature of internet memes must reflect and/or illuminate some aspect of the targeted audience[s] and their respective beliefs, values, and/or sensibilities. They play upon “preexisting social and cultural constructs; norms; values or specific environments” in order to be successful at both transmitting their idea and being shared ( Benaim, 2018 , p. 901). They must utilize specific lexicons, symbols, and ideas within the [sub]culture to spark interest among those that share a form of common identity. This same rule applies to traditional methods of PSYOPs as well, “different lines of persuasion and symbols will need to be developed or selected to influence the [target audiences] to achieve each of the different [supporting Psychological Operations objectives]” ( US Army, 2003 , p. 5–2). Otherwise, much like the aforementioned cartel held Mexico example stated, they will flounder in their attempts of disseminating within and outside of their target audience.

Humor has oft been cited as one of the primary functions of internet memes ( Piata, 2016 ; Ross and Rivers, 2017 ; Benaim, 2018 ). Being known as such among the general populace internet memes may be simply brushed aside as a joke rather than sincere ideological, informative, or political commentary of the meme sharer. Although it should be noted this may indeed be the end goal of many internet memes to begin with: a brief chuckle to add a bit of spice to life or a cathartic aid. This aspect of humor may also aid in the propagation of the internet meme continuing its dissemination and that can be later capitalized upon (via audience building) until it finds an audience that embraces targeted ideas as axiomatic.

The ability of memes to be created and disseminated quickly makes them an effective instrument of information propagation. During national or worldwide events memes will appear across social media platforms; displaying their timeliness in novel fashion. In 2016 political memes revolving around the U.S. election swept the internet along with memes of Harambe the gorilla ( Haddow, 2016 ; Judah, 2017 ). In 2020, internet memes referencing the spread of COVID-19 (particularly relating to the rush on toilet paper, political leader's stance's on the disease, and “cures” in the U.S.A.), presidential candidates (including President Donald Trump, Bernie Sanders, and Joe Biden), economic and social policy, and anti-vaccination are all commonplace on social media platforms. Meme creators and those that share them can (and do) in real-time, with minimal fear of social backlash or censorship. The efficiency of their production and range parallels that of aerial leaflet propaganda; information falling out of the sky and into the minds of those who happen to come across it: with little fear of “enemies” halting its immediate affects. The primary differences lie in internet memes ability to be up-to-the-minute, anonymous, malleable, and capable of being harnessed by the individual. The following section will discuss in more detail why they are useful for spreading ideas, particularly those relating to politics, social issues, and more pragmatic subject matter due to the option of meme smith's anonymity.

The Death of the Meme Creator: Enter the Remix

The ability to create and disseminate quickly aids in the anonymity of the source of memes; be they State actors or private individuals. Ross and Rivers, as well as Cannizarro, note that internet memes encourage the anonymity of their origin and empower those who would not otherwise likely engage in political or confrontational dialogue, regardless if the information is based in factual evidence or not ( Cannizzaro, 2016 ; Ross and Rivers, 2017 ). In brief, part of the draw of internet memes for many people (those creating or sharing them) is their ability to remain constantly contemporary through continual remixing and anonymous creation.

The “death of the meme creator,” to borrow from Roland Barthes', The Death of the Author , erases the problematic notions of creation (i.e., who created it and the creator's truth behind it) and allows for sharing and remixing to be a community based exercise in liberty. As Barthes writes, “the explanation of a work is always sought in the man or woman who produced it,” but without a face or name to turn to the internet meme exists in a permanent state of inference and translatability; an object protean by nature ( Barthes, 2010 , p. 1322). Those who share or remix internet memes are not held to a standard or a limitation of the author who created it. The internet memes meaning lies not in the mind or stances of the meme creator, but that of its destination, the meme consumer. The limit is only that of imagination and its ability to stay temporally trendy.

The ability to immediately separate the creator of the meme and the meme itself adds a curious level of freedom to interpret the meme. In a Pew Research study, “U.S. Media Polarization and the 2020 Election: A Nation Divided,” notes, “evidence suggests that partisan polarization in the use and trust of media sources has widened in the past 5 years” primarily due to distrusted sources of information ( Jurkowitz et al., 2020 ). As media finds itself in an age of increasing media polarization memes offer information dispersion that generally lack an obvious political point of origin. Internet memes are a generally authorless product freeing their audiences from the shackles of authorial expectation. This allows for multiple levels of understanding to emanate from the locus (the meme) aiding in the enjoyment, befuddlement, catharsis, or manipulation in the marketplace of ideas. As there is generally no author/creator to utilize preexisting political biases audiences who come across political memes have a chance to view them without their own bias filters on guard. In short, the language itself and the impression left on the minds of the audience that generate their own meanings and understanding of the meme.

It is here that memes diverge from analog leaflet propaganda. Although the exact creators may not be known the targeted audience is aware of their point of origin. This creates a much more difficult task for the traditional propagandist. Internet memes aided by symbolism, cultural understanding, and accurate audience targeting utilize the death of the meme creator to manipulate audience heuristic understandings of the world. In order to do so it must first cast a wide net through trendiness and remixing ideas that are attractive to a target audience.

To maintain their trendiness internet memes must create or capitalize upon a culture's symbolic value archetypes in real-time. Benaim writes, “Internet memes are far from simple regressive online production, since they incorporate high symbolic values from a lead culture” ( Benaim, 2018 , p. 904). By taking aspects from the real world and placing them into internet memes they create new meanings, symbols, language, and knowledge ( Benaim, 2018 ). These creations are not novel but rely on “samplings” (to steal a phrase from the music industry) of culture therefore creating a novel take on the idea or event. Ross and Rivers note the ability of people to contribute to the meme writing, “creators are able to either alter the specific meaning to be expressed through the text or to create a new iteration of the meme or to change the image and the text to create a new derivative meme entirely” ( Ross and Rivers, 2017 , p. 2). This leads to greater participation within the culture or linguistic group of the memes referential material.

Although many meme smiths prefer to remain anonymous there are some who prefer to make themselves known via social media pseudonyms. One particularly striking example is of Twitter user “CarpeDonktum” who visited the White House as part of President Donald Trump's “Social Media Summit” in July of 2019 ( Relman, 2019 ; Roose, 2019 ). This is perhaps evidence of an emerging market for meme creators within political and social spheres of society: but, for now, it remains a unique example swimming upstream among the anonymous masses generating memes today.

The greater potential for remixing and/or creates an opportunity to take power out of the hands of State entities or corporations and places it in the hands of small groups and/or individuals. To highlight this advantage, there is a low entry barrier for anyone willing to participate: and they do. Lessig, referring to the growth of participation in creating memes, writes, “This means more people can create in this way, which means that many more do. The images or sounds are taken from the tokens of culture, whether digital or analog” ( Lessig, 2009 , p. 71). In the past such activities would rely heavily on high dollar advertisement campaigns, physical materials, and substantial brain and manpower. No longer are planes, paper, and people trained in psychological warfare necessary to propagate leaflet propaganda; all it takes is an individual, an Internet connection, and the understanding of a target audience. Once a target audience has been determined internet meme creators with malevolent or mischievous intent utilize cognitive biases to garner further influence.

Heuristic Attack of the Memes

The human brain can only handle so much conscious information at a time. It uses heuristics to help people navigate through the world without devoting too many cognitive resources to do so. Psychologist Christopher Dwyer, paraphrasing the work of West, Toplak, and Stanovich, notes that, “heuristics allow one to make an inference without extensive deliberation and/or reflective judgment, given that they are essentially schemas for such solutions” (as cited by Dwyer, 2018 ). These heuristic properties of human thinking can be exploited leading to cognitive biases. These biases can be effectively gamed by internet memes and the people or groups which create and share them. There are several keystone biases at play in viral memes: confirmation bias, homogeneity bias, and popularity bias. Each uses their own specialized tools to propagate misinformation and propaganda. In addition they also help craft the [de]legitimization of ideas, people, and social movements.

Confirmation bias focuses on the things and ideas people find to be agreeable or sensible to their respective worldview. If information aligns with previously held beliefs, be they true or misplaced, they are more likely to believe it. Shahram Heshmat, writing in Psychology Today , states, “Once we have formed a view, we embrace information that confirms that view while ignoring, or rejecting, information that casts doubt on it ( Heshmat, 2015 )”. The bias takes on a 2-fold purpose, reconfirming one's initial stance on an idea and discriminating against ideas that do not reconfirm it. This bias allows for an echo chamber of ideas to be consumed and shared throughout the web ( Ciampaglia, 2018 ). Facebook has highlighted the malevolent use of this bias in press releases after the 2016 U.S. presidential election.

Facebook, in a public release, noted the use of this bias in false amplification of ideology driven Facebook pages. Facebook defined false amplification as, “Coordinated activity by inauthentic accounts with the intent of manipulating political discussion” the goals being, “discouraging specific parties from participating in discussion, or amplifying sensationalistic voices over others” ( Weedon et al., 2017 ). The public release also notes that false amplifiers can be “professional groups” targeting specific demographics or “a smaller number of carefully curated accounts that exhibit authentic characteristics with well-developed online personas” giving power both to States and institutions as well as the individual or small group ( Weedon et al., 2017 ). These tactics mirror conventional PSYOPs tactics. Traditional methods use by PSYOPs to disseminate propaganda, including leaflet propaganda, utilize “primary groups” and/or “secondary groups” to achieve the goals of their operations.

Primary groups, “prefer to receive information from other members in the group and tend to shun information from outsiders,” making for easy audience targeting due to the inherent echo-chamber structure of the group ( US Army, 2003 , p. 3–5). The caveat of such targeting is that these groups generally do not have mass influence in the public sphere. On the other hand secondary groups consist of large numbers of people and viewpoints bonded together through a common objective or idea. Secondary groups can be manipulated via aggregation, based on physical location, or through the medium of a key communicator (e.g., celebrities, politicians, authority figures, etc.). Furthermore, due to the variability of viewpoints and backgrounds secondary groups freely use and disseminate information from sources: casting a larger net for prospective target audiences ( US Army, 2003 , p. 3–5). Succinctly, contemporary memes mirror traditional PSYOPs through their use of false amplification via digital key communicators. Be it a meme page, a celebrity's Twitter account, or a teacher's Facebook page memes are able to utilize their respective position in society to [de]legitimize ideas and people. Once information has been disseminated and accepted (as either inherently true or false) further solidification of in-group bonds becomes a likely outcome. Regardless of the size and scope of those behind the page they all utilize a combination of sensationalist “news,” internet memes, and other forms of information dissemination to try to alter the political and social discourses taking place on their medium ( Weedon et al., 2017 ). The confirmation of one's ideas can be a powerful tool. Allowing for one to feel accepted as part of an “in-group.” These “in groups” can be comprised of nearly any point of view and appear across social networks creating social bubbles based on a homogeneity bias.

Statistical data confirms that social media platforms are ripe social bubble fields ready to be tilled until their cognitive bias crops bear their harvest. According to Schmidt et al. users limit their activity to a small number of like-minded Facebook pages resulting in severe selective exposure ( Schmidt et al., 2017 ). Furthermore, users confine themselves to a select range of pages or news outlets that quite often aid in reconfirming their beliefs and ideas ( Schmidt et al., 2017 ). Such pages utilize memes (particularly image macro memes) to reconfirm and disseminate their pages respective point of view or guiding ideology. In short, social media users are bolstering their own claims and cognitive biases based upon what they already believe to be true. This aids in limiting their personal worldview and, on a grander scale, in participating in strong user polarization across the globe.

Nikolov et al. (2015) , in Measuring Online Social Bubbles , found that users of Twitter and email are limiting their access to information, in regards to the range of their sources, in comparison to a general search baseline; once more aiding in the [re]confirmation of ideas. While this may be trivial in many instances of internet memes, these can serve as legitimate forms of propaganda aided by the algorithms, used by search engines and social media alike, to show users more of what their platform behavior indicates they prefer. By limiting oneself in the pages they view, the internet memes and news sources they gain insight from, and the lack of diversity of ideas encountered, users may be inadvertently handicapping their understanding of objective reality; leading to the potentially more dangerous activity of political astroturfing.

Political astroturfing paves the way to gather large numbers of people into social bubbles and instigates a popularity bias. Ratkiewicz et al. defines political astroturfing as, “political campaigns disguised as spontaneous ‘grassroots' behavior that are in reality carried out by a single person or organization” ( Ratkiewicz et al., 2011 ). As previously mentioned internet memes are easily created, shared, and remixed making them a malleable tool for States and individuals with an ideological imperative. By utilizing internet memes and other digital tools such groups can effectively create and organize large groups of users into social bubbles that act as echo chambers ( Weedon et al., 2017 ). These pages or users are initially works of fiction with the guise of reality. As users are targeted (through advertisements or user behavior patterns) the pages targeting users become populated with real users; disguising the malevolent intent behind the page's creation. Utilizing a popularity bias, users may no longer invest time and effort into fact checking the information disseminated by such pages.

The fainéant nature of users throws fact checking and verification into the wind stirring up a typhoon of misinformation that can quickly spread across the Internet. Rather than the internet memes credibility or truthfulness it is its, “catchiness and repeatability [that] can function as the primary drivers of information diffusion” ( Ratkiewicz et al., 2011 ). To put it succinctly, internet memes ability to entertain or be easily remembered give it greater claim and viral ability than its accuracy. Notions of what is true, or even remotely possible, lie in wait within the heuristic properties of the internet memes. Similar tactics were used, revised, and iterated in the creation and dispersal of leaflet propaganda as partially discussed in section Thought Bombs Raining Down From Above of this article. Although leaflet propaganda (and by extension memes) that inhabit the realm of possibility can be accepted as truth, the truth itself may appear unbelievable by target audiences.

This notion of catchiness and repeatability echoes the tactics of Allied World War II leaflet propaganda. Martin F. Herz notes that slogans such as “Better Free Than Prisoner-of-War, Better a Prisoner-of-War Than Dead” proved effective in manipulating the behavior and ideas of the enemy combatants” and helped to maintain operations security (OPSEC) within the allied forces with the phrase “loose lips might sink ships” (see Figure 3 ) ( Loose Lips Might Sink Ships, 1941 ; Herz, 1949 ). Also in the Korean War statements such as “A live patriot can help Korea more than a dead one” were common in aerial leaflets dropped over enemy territory; giving a simple, repeatable maxim to the target audiences ( Psychological Warfare in Korea, 1951 ). Furthermore, in interviews with the US Fifth Army's POWs in Italy they found that claims that are factually truthful could appear to be outrageous claims by enemy combatants. The example cited is that all POWs “received eggs for breakfast,” while true, POWs claimed that, “This idea was so preposterous to Germans on the other side of the firing line that they simply laughed at the idea” ( Herz, 1949 , p. 473). In order to be effective manipulation tools (be they leaflet propaganda or internet memes) they must walk a fine line between reality and believability.

Figure 3 . Oregon Trail Toilet Paper Meme (2020) .

Utilizing heuristics and cognitive biases have aided humans in their survival as well as their gullibility. As of January 2020 the number of active internet users worldwide is nearly 4.5 billion opening the door ever wider for the use and spread of internet memes for malevolent purposes ( Clement, 2020c ). In the realms of politics and ideology these tools are often combined to [de]legitimize ideas, political candidates, and social movements. The aforementioned keystone biases aid in building tribal bonds and create “Other” groups that compete for information dissemination domination among the meme marketplace. Much like the propagandists mentioned in section three groups will use, remix and iterate the malleable form of the image macro meme to “combat” ideas not supporting their narrative through the tools of [de]legitimization.

Internet memes, along with their previously mentioned targeting biases and tools, can act as agents of [de]legitimization. Legitimization works to shine a positive light on an idea or person by highlighting the good qualities inherent in the subject. Delegitimizing focus on finding the negative components; but also aids in the “Othering” of groups who may find said ideas to be a positive thing. Ross and Rivers note this quality among internet memes writing, “delegitimization demonstrates the absence of rhetorical alignment with the prevalent social values of the time in addition to the absence of positive, beneficial, ethical, understandable action” ( Ross and Rivers, 2017 , p. 3). It takes no stretch of the imagination to understand how this can play out in the digital world.

By finding like-minded people and utilizing the cognitive biases built into the social media construct the reality of a given situation can take on a phantasmagoric form. Each person delves further into their own hand tailored version of reality, legitimizing information that agrees with their preconceived notions and finding delegitimizing information (that agrees with their stance) as further evidence of their worldview being correct. By finding other people or groups who share similar dispositions an idea of an other will emerge. This strategy is not novel. Politicians, governments, and companies have used it since time immemorial. The medium has simply taken on a viral form now capable of being wielded by States, institutions, corporations, and individuals alike.

For instance, the U.S. Army noted that a target audience with “needs, wants, and desires… will, at varying levels of effort, strive to satisfy them” ( US Army, 2003 , p. 5, 6). If the desire is to have a voice, to spark change, or to express oneself and their opinion every person now has a medium to do so. In addition, “The desire of the [target audience] to fulfill, alleviate, or eliminate a need provides the motivation for them to change their behavior” ( US Army, 2003 , p. 5, 6). By exploiting the needs and heuristics of target audiences the creators of memes, particularly those with malevolent intentions, can expand their reach across the globe and create tribal groups without the necessity of people actually being in a geographic location. People are given a “weapon” and a means to alleviate their needs, but they may be inadvertently letting someone else aim. The needs of a group can take the form of micro or macro behaviors on the Internet and/or the real world and need only a singular point of agreement to begin forming Othering tactics. Guttormsen, notes on the scope of boundary markers that can lead to Othering range from supra-national to local and include the realms of the “political, cultural, social, professional, and legal spheres” ( Guttormsen, 2018 , p. 324). These realms may only need a single act of meaning-attribution to a person, group, or idea to set in motion the gears of Othering ( Guttormsen, 2018 , p. 326). Once the gears have been set in motion it raises the possibility of subjecting itself to the aforementioned cognitive biases resulting in the sharing of flawed information via internet memes; perhaps further distancing groups viewed through polarizing lenses. The following section briefly displays several notable examples of how these strategies have played out in the real world.

Memes in Action

The use of internet memes to try and alter the thoughts and actions of people has become better documented over the past decade. This section is devoted to several real-world examples of internet memes at use, by both States and individuals. One of the most studied instances is in relation to the Internet Research Agency (hereafter IRA) and their role in cyber influence operations. It should be noted due to the vast amount of research available for each respective example the following selection of real-world actions given are intentionally succinct and meant to be a cursory gander at how internet memes have been used in the real-world.

The IRA appears to have had several goals including a long term “social influence operation consisting of various coordinated disinformation tactics aimed directly at US citizens” with the goal of, “exert[ing] political influence and exacerbat[ing] social divisions in US culture” ( DiResta et al., 2019 ). In 2016, alone the IRA generated or repurposed over 167,000 memes on Facebook and Instagram with millions of user interactions across platforms focused on the organic communities they had created over time ( DiResta et al., 2019 , p. 51–58). Each page operated by the IRA was specifically tailored to targeted audiences focusing on polarizing issues, public figures, and identity ( DiResta et al., 2019 , p. 11). Religious, minority, and political groups were heavily targeted for their ability to create echo chambers. Furthermore, posts created by these pages began with producing narratives such groups may find appealing, disseminating them using targeted advertisements, and eventually posts that “intended to elicit outrage” and real-world action ( Howard and Liotsiou, 2018 , p. 19). In order to increase the number of potential users viewing their content these pages would initially rely heavily on internet memes focused on humor to create organic interactions. For example two IRA created Facebook pages, Army of Jesus and Christian Mothers Against Masterbation, focused on religion and sexual addiction. One popular meme, focusing on masturbation, was made and remixed multiple times and initially shared via Facebook and Instagram. The meme featuring apparent depictions of Jesus Christ reads, “Struggling with the addiction to masturbation? Reach out and we will beat it together” ( DiResta et al., 2019 , p. 40; Jesus- We can beat it together, 2016 ) (see Figure 4 ). This meme utilized a real-world issue in conjunction with a sexual pun leading to content being shared by its targeted and non-targeted audience alike ( DiResta et al., 2019 , p. 40). By doing so it increased the likelihood of reaching targeted audiences via non-targeted audience participation; furthering their purpose in the long run by increasing interactions and page visibility.

Figure 4 . Liberal Logic Meme (2020) vs. MAGA Logic Meme (2020) .

The dense modality of their memes aided in the viral spread by pandering to their target audience via reinforcement of views, interaction by those criticizing them, or people who simply found them funny. All of which aided in their organic spread helping to increase the anonymity of their origin and their opaque goals. The continued use of such tactics hints that those creating and using them are finding them useful to their purposes. Through the use of the aforementioned cognitive biases as well as other strategies the IRA created a definite footprint on the internet and digital culture. Another instance of memes altering the dialogue around an issue can be found in Croatia and the Caća se vrača meme initiative surrounding former Prime Minister Ino Sanader.

Bebić and Volarevic studied the spread the influence of Caća se vrača (the father is coming back) in Croatia finding that memes “may have influenced the media reporting,” in regards to [re]legitimizing Ino Sanader after his release from prison ( Bebić and Volarevic, 2018 , p. 53). Their data suggests that Sanader's public opinion went from neutral to positive in news broadcasts following the satirical-meme initiative. Piata found similar results in the Greek elections of 2015. Through the use of metaphor and humor both political parties utilized social media and memes as tools of [de]legitimization ( Piata, 2016 , p. 53). Using the popularity bias implicit in their respective messages nabufested in increased communication between targeted and non-targeted audiences. Corporations have also been subject to the attacks of individuals and groups via internet memes.

Ross and Rivers, highlighting the work of Davis et al. (2016), exampled Greenpeace's “Let's Go!” campaign and their use of internet memes to delegitimize Shell Oil company's advertising via irony. One example's background picture features an oil platform and the superimposed text reads, “Because fuck you, earth. Let's Go” ( Ross and Rivers, 2017 , p. 4). Remixing a company's advertisement campaign to display irony was a novel approach to internet meme information dissemination; taking the power away from a large corporation and placing it in the hands of those concerned with various social and environmental issues. This meme series also created the foundation necessary for Othering and delegitimization of the corporation by playing with the catchiness and repeatability allowing the memes greater likelihood of dispersal among targeted and non-targeted audiences. This trend continues today and can be seen being created and disseminated by individuals in regards to the COVID-19 pandemic.

Much like any other large socially relevant event the COVID-19 pandemic has created an assemblage of memes revolving around it. Many memes being produced focus on the humor or puerile attempts of people to be prepared for social distancing, protecting themselves, or panic buying. Common memes being shared have highlighted the panic buying of toilet paper, misinformation regarding how to “cure” or inoculate oneself against the virus, and the use of nationalist based rhetoric and the responses of political leaders and other secondary individuals/groups to its spread.

One example from Covid-19 Archive, but originating Facebook, uses a screen shot from Twitter featuring the popular 1974 computer game Oregon Trail depicting an ox pulling a wagon that looks like a roll of toilet paper. Underneath of the wagon, remixing the same script and style as the game, it states, “You have died of Corona Virus.” Above the static image the superimposed script reads, “You failed to hoard enough TP [toilet paper]” ( Oregon Trail Toilet Paper Meme, 2020 ) (see Figure 5 ). This particular meme pays tribute to a game initially created to educate people about the hardships faced by those traveling the length of the country in the 1,800 s. It ironically compares it to the “struggles” and “dangers” faced by people living in the twenty-first century without enough toilet paper; a theme many audiences may find humorous. Furthermore, it makes it contemporary by including the toilet paper imagery, highlighting the absurdity of the toilet paper hoarding phenomenon of early 2020, and commenting on the power of fear to inspire action within a populace. This meme appears intent on utilizing humor to point out the absurd rather than a call to action. Though other memes have begun ideological Othering tactics.

Figure 5 . PsyWar Leaflet Archive - 141-J-1 (2012) .

Another example shines a spotlight on the aforementioned tactics and strategies of memes and their counter-memes. In mid, 2020 memes began appearing across social platforms (including, but not limited to, Reddit, Facebook, 9gag, and Twitter) memes depicting opposing viewpoints about Dr. Anthony Stephen Fauci and Dr. Stella Immanuel ( Liberal Logic Meme, 2020 ; MAGA Logic Meme, 2020 ) (see Figure 6 ). The memes mimic and remix each other in multiple iterations underscoring the various [de]legitimizing characteristics of each for their targeted audiences. In the “Liberal Logic” meme Dr. Immanuel's photo is positioned on the left (placing her first for audiences who read and view documents left to right) and her experience in the field leading to “successfully cur[ing] hundreds of patients with corona virus” is touted as proof of her position as an expert worth believing. This is followed up by the opposing viewpoint “we don't trust her” underneath. On the other hand, Dr. Fauci is painted in a malevolent light positioned on the right (leading the reader to be lead into the claims about Dr. Fauci only after seeing Dr. Immanuel's posited position) noting previous claims as his position as the director of the National Institute of Allergy and Infectious Diseases (NIAID) in the early days of the COVID-19 response. Furthermore, one more example of audience targeting enters the claims against Dr. Fauci noting, “and believes that fetuses aren[‘]t alive”; an added bonus to target a pro-life audience in which the message may further resonate. Underneath his photo is the statement, “real doctor” intended to be meant sarcastically.

Figure 6 . World War Two US internal Propaganda leaflet.

On the opposing side of this example is the “MAGA Logic” meme. Note the reversal of the photos (Fauci is now on the right) and Dr. Fauci's experience as an infections disease expert for half a century is highlighted with the statement, “I don't trust him…” underneath. Dr. Immanuel is positioned on the left featuring statements that delegitimize her stances seen in the aforementioned “Liberal Logic” meme including the notion that “alien DNA is used in medical treatments” with the phrase “She's a doctor” placed underneath. These two examples are a brilliant display of the mirroring capacity of memes and counter-memes and their aforementioned targeting strategies at work. Each specific meme is targeted for their intended audience, utilizes modality to convey layered meaning, utilizes contemporary culture and society as a reference point, is up to date with the current news cycle of information that meme consumers will most likely be familiar with, and helps to solidify the tribal bonds and their implicit heuristics.

Another example bases its premise on the origin of the COVID-19 virus. The meme archetype has been dubbed the “China Virus” meme appearing after President Donald Trump began referring to COVID-19 as such in March 2020 ( Viala-Gaudefroy and Lindaman, 2020 ). Memes based around this archetype typically use a zoomed in photo of President Trump's notes at a press conference. His left hand is visible appearing to be saving the line in which he is reading from. An even further enhancement displays an edit in which “Corona” has been crossed out and “Chinese” has been written above it, formulating the phrase “Chinese Virus” ( Chinese Virus, 2020 ). This screen shot was, shared on social media as well as in traditional media mediums, remixed across media platforms, and has become a popular referential phrase in the social consciousness. Unlike its analog predecessor such massive distribution and rhetorical effect could only be dream of for the propagandists creating aerial leaflet propaganda in the past and present theaters of their dispersal.

The usage of the phrase has created a dynamic labeling the virus and its origins as a way to personify it as a foreign impurity and allows those affected globally their to focus their collective angst toward. The meme acts as another method of dissemination along with other forms of medias. Although the virus does indeed appear to have originated in Wuhan, China the effects of such rhetoric are felt by Asian-Americans. In the United States between March 19 and April 15, 2020 1,497 discrimination complaints were filed in relation to interactions revolving around COVID-19 ( Zhou et al., 2020 ). Although there was no direct call to action based on the meme and interactions may be coincidental, the effects of the meme on rhetoric within the social consciousness are verifiable. This particular meme archetype could be used for further research opportunities in exploring correlations between trending internet memes and real-world interactions. As the virus runs its course and people continue to react internet memes will indubitably play a part in the public perception and reaction to COVID-19 and any further large scale events.

Final Discussion

Relatively cheap computing power and the Internet have led to the great collection of peoples cast under the banner of a globalized humanity having greater access and agency among each other than any previous time in history. Despite the great possibilities of such technology the same tools that have found success in bridging the gaps between differing peoples and cultures have evolved to fit the times. Tribalism, in the various forms it takes, still remains as part of the human condition and there are individuals, corporations, and state affiliated actors willing and able to maliciously exploit the newly found bridges between differing peoples. Internet memes have become the digital successor of leaflet propaganda and look to be the first digital version in the evolutionary sequence of things to come. Their ability to harness viral modality, prey upon heuristics and cognitive biases, and be exploited by corporations, nations, political parties, and individuals alike changes the historical power dynamic. In some ways internet memes level the playing field and in others they open the door for an era of mass digital manipulation.

This article has highlighted the facets of memes as the digital modern leaflet propaganda, but while in doing so a number of research possibilities have been discovered. More contemporary academic research into the role and effectiveness of contemporary aerial leaflet propaganda in the digital age is sparse. This opens lanes of research that prior scholars not competing with the dispersal properties of the internet could not have had insight into. There is also a dire need for further research into how [blatant] misinformation can be combatted by both platforms and individuals. Also, research into digital public reactions (via internet memes) during times of global panic could shed light on how and why people react to international stresses, particularly in areas of catharsis and personal empowerment. Furthermore, strategies to track viral memes across platforms could offer valuable insights into the collective digital consciousness of the twenty-first century. Historically based tracing of the evolution of memes and their use of technology (i.e., newspapers, radio, television) may offer insights into the future praxis. Unfortunately, due to the great wealth of data stored privately by social media companies and governments it appears to be nearly impossible to study these phenomena in real-time. As stated as a concluding thought to Psychological Warfare in Korea 69 years ago, “In psychological warfare we have an inexpensive, effective weapon that is bound to prove more effective as we continue to learn to perfect our technique” ( Psychological Warfare in Korea, 1951 ). As the techniques and targeting power of meme creators bent on goal orientated information dissemination, to alter the hearts and minds of people globally, the effective weapon of aerial leaflet propaganda has become potentially even more effective in its digital iteration the internet meme. Perhaps for the time being its best to try to have a laugh at the times and share some internet memes. For now perhaps it is best to enjoy the laugh for the world of tomorrow may look back and find internet memes to be nothing to joke about.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Author Contributions

JN contributed to the design and implementation of the research topic, to the analysis of the results and writing of the manuscript.

Conflict of Interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords: internet memes, leaflet propaganda, heuristics, social media, digital propaganda

Citation: Nieubuurt JT (2021) Internet Memes: Leaflet Propaganda of the Digital Age. Front. Commun. 5:547065. doi: 10.3389/fcomm.2020.547065

Received: 30 March 2020; Accepted: 19 November 2020; Published: 15 January 2021.

Reviewed by:

Copyright © 2021 Nieubuurt. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Joshua Troy Nieubuurt, joshua.nieubuurt@faculty.umgc.edu

This article is part of the Research Topic

The Age of Mass Deception: Manipulation and Control in Digital Communications

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Have social media’s ‘hot takes’ and memes replaced genuine, well-written discourse.

We ask a father and daughter for whom writing is central to their lives.

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This week marked the anniversary in 1776 of Thomas Paine publishing his pamphlet, Common Sense . In 47 pages, he advocated for independence from Great Britain through clear, persuasive writing.

Now, nearly 250 years later, we have a lot of people who are more than happy to share their thoughts, often in plain and not very impressive prose, and usually in reductive and pithy sentences, memes, or emojis.

That left us wondering: Are we losing our ability to write compelling, elaborate, but clearly thought-out and persuasive essays? Are social media threads the closest we get now? Have we abdicated the high ground of quality intellectual discourse in favor of "hot takes?" Is there space anymore for well-crafted, highly sourced, idea-provoking language that doesn't just pander to a bubble, but challenges our strongly held beliefs? And if there is, who is in that space writing it, and who's reading it?

In the audio above, we talk it over with Raj Mankad , the deputy opinion editor at the Houston Chronicle and co-founder of Grackle and Grackle Literary Enterprises , which teaches and consults on creative writing. Also with us is Raj's daughter, Lila Mankad, a published poet and senior in the creative writing program at the Kinder High School for the Performing and Visual Arts.

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Chapter 6: 21st-century media and issues

6.4.1 Communication through memes (argument from experience)

Alexander Caldwell

English 102, February 2021

What makes a person laugh? Could it be clowns, cat videos, or comedians? Something that makes me laugh is memes. Memes are humorous texts or situations that people share online. People have different opinions about memes, some positive, some negative. Regardless of the matter, I believe the history of memes has led to new online social interactions, new vocabulary to the English language, and the continuation of literacy through the communication of memes.

From my understanding, memes originated from vines. Vines were usually live-action shorts where individuals would do or say something humorous or relatable. These vines would then be popularized on YouTube and other social media. This growing group of vine viewers and producers created a new social cluster of people. It is far from an organized group, but this cluster of people began to communicate interests, hobbies, and relatable moments through the usage of vines. This cluster of people can be joined and existed as with the blink of an eye, it all depends on one’s communication to being online and involved in online humor. This includes viewers as well. Many people in modern memes like to refer to this cluster as “the internet.” While it is true that a massive amount of people online view memes, some people like to use the internet strictly for business, so this term does mean the whole internet. Through the use of vines, more people joined “the internet” and became familiar with the idea of posting shorthanded humor online. During the era of vines, I was not currently literate on social media. At the time, I had only heard of vines through the chatter of other people. These vines related to my literacy because this was the time where I started to also take note of online humor. I noticed that an individual in-person could be funny, but so could that same person online. This expanded my definition of the genre of humor.

Although vines were well enjoyed by the internet, their time of glory soon came to an end with the new era of memes. It should be noted that this transition took time and did not happen immediately over the internet. Rather, each new era of meme phases out old meme eras. The new era of memes is what I describe as the drawn meme age. This was most certainly one of the longest existing meme eras and it includes many iconic memes still occasionally enjoyed today. The era was constructed by memes that appear to be extremely simple drawings of human emotions. Drawn era memes are almost always accompanied by a short text and might include panels, similar to how a comic book reads. Popular drawings include the troll face, le gusta meme, and like-a-boss stick figures (see figure 1). These drawings, combine with their text, allowed content producers to convey exaggerated or enhanced emotions to their audience. Another term for a content producer is what many like refer to as a memer or meme lord if one wants to go that far. This drawing era is a stark contrast to the vines because a memer can keep their anonymity, while in vines people are required to share their visage. The drawn era was truly when I started to be an active consumer of memes. I enjoyed the quick-witted puns that these memes provided. Sometimes, I would spend hours just looking and reading these memes. The troll face memes were by far my favorite. I remember saving the troll face icon in my photo library so if I ever wanted to use it in a text chat, I could. Whenever someone in my texting group sent a troll face to one another, it usually meant that they did something funny, or their previous comment was just a joke and should not be taken seriously. The drawn era offered plenty of other memes, like the troll face, where anyone could copy the image and use it to express an emotion, similar to an emoji. This form of communication was unique in my eyes and enjoyed by others who used memes to communicate in a group text. These communications were all possible because of the drawn era memes.

Although the drawn era was through the internet, another era was happening as well. Circa the drawn meme era, there was what I like to call the classic meme era. This era often exhibited memes that are single panel, contain white font with a black border, and an image in the background (see figure 2). The images often were reused, but contained a similar ‘base emotion,’ while white font added a new context to that image. The Classic era, similar to its sibling, the Drawn meme era, did last for a longer amount of time, but unlike the Drawn era, most of the Classic era memes are considered dead or outdated by the internet. It is common practice that a dead meme ceases to be posted because they create an unsettling feeling in the audience. The reason why this practice exists is somewhat of a mystery but can slightly be explained by the fact that people do not want to see the same meme repeatedly. This phenomenon fosters new memes but also forces memers to adapt to new eras or risk their popularity. It should also be noted that while the internet as a whole might view a meme as dead, small groups of the internet might still enjoy a meme, making the meme live in that respective group. I understood the Classic era of memes as one of the easiest ways to communicate day to day situations. This was also the era where I noticed, in my friend-group-chat, that memes soon became competitive. To elaborate, everyone in the group chat would try to have the funniest meme posted last. This communication led to a string of nothing but memes being communicated from each person in the group chat. The point of doing this was to seem like the funniest person in the group by finding the funniest meme.

Over time, more and more people became dedicated to memes. Many personal social media accounts have participated in the sharing of memes by this time. While the internet embraced the sharing of memes, some memers noticed that their work was being copied. If the meme were stolen, with no credit given to the creator, memers would consider the stealer a meme thief. In modern times, most people do not care about whether they stole a meme or not because everyone did it at some point. However, during this era, people were passionate that their work was not stolen. This next era is the clone era. The Clone era is what appears to end in the classic era. Due to the many social media accounts active in the internet cluster, the hassle of making a white font with a black border seemed unnecessary for many and the style of classic memes was all dying. This brought the new age of cloned memes. These memes often use simple fonts and often include a popular person or character. What made their era completely unique from other eras was the uniformity of the memes. The best example of this era would be the spongegar meme (see figure 3). This meme was on every major memer’s page. Despite having different text and different context, every memer would clone a template of this specific meme. Due to the consistent reuse of the same meme template, clone era memes often died faster than most. If a social media site were to be lagging even a few days behind others, this could result in a Clone era meme being dead before it fully reaches other social media platforms. A good example of this is the Uganda Nuckles meme. Only a few days after the meme fully arrived on Instagram other meme viewers were already showing distaste for the meme, declaring it as dead while hopping onto a new meme. This hypercycle of picking up and dropping memes is what is suspected to believe what caused the collapse of the Clone era memes. Like all other memes, the Clone era memes also relate to literacy. Clone era memes, I noticed, in the comment section self-promoting became more popular. I often would find memers commenting on other’s comments try to rake up followers and make themself more noticed.

Shortly after the collapse of the almost-meme-empires from the clone era, the memers realized that using a clone is acceptable but it is not a viable method if everyone uses the same meme template. This caused a new wave of memes, often referenced to as the collapse meme. Collapse era memes have very little in common except for the fact that some were particularly bizarre. The best example of the would be the E meme (see figure 4). This meme was an unusual edit of Lord Farquaad, Mark Zuckerberg on trial, and a YouTuber named Markiplier. The E text provided no real understanding and neither did the image. Despite this, the meme became popular and was amusing for its moment of fame. The Collapse era itself was brief but a few Collapse era memes are still being produced today. I noticed that the comments on these memes were often unappreciative of these memes, many questioning how memes even evolved to such a low point. My high school friends and I found these memes funny, but not for a very long time. We would often, in a text group chat, share a Collapse era meme, only for someone to argue the point that “it wasn’t funny.”

The final era is what is going to be called the Modern era. This era stands apart from other eras due to the sheer diversity of memes. This era started circa before the Clone era and is still in effect today. Modern era memes include video memes, gif memes, Tik Tok memes, movie quote memes, dark humor, as well as semi-cloned memes. Modern era memes will also borrow memes or make remarks from previous eras. The modern era of memes survived through different eras because of their ability to adapt and be diverse. This meme diversity also makes the life span of a meme much longer than how other eras would have treated it. A good example is the Chad meme. This meme was always humorous due to its exaggerated context and its vast diversity of artwork. Despite the fact Chad meme is no longer in its prime, Chad memes are still made today, and they have not been declared dead. The modern meme also excels at sharing points of view, whether it be political, the relationship between a girl and her boyfriend, or between the United States and Canada.

The modern era of memes is where I started to make a few memes for myself. The modern era memes that I made were always directed to a specific interest group. An example that I have is this Clash of Clans meme. The meme is special because only a person who actively plays Clash of Clans would fully understand what I was communicating. Through communication of modern memes, I also noticed that I could use these memes as a video game and movie review system. A good example of this is the recent game Cyberpunk 2077. I was considering getting the game when suddenly I saw a new flow of memes revolving around the game. All the memes pointed to the flaws in the game, such as poor graphics, bugged physics, and flawed logic. Through the communication of memes, I learned that Cyberpunk 2077 was not a well-programmed game and decided not to buy it. Another way I use memes is to communicate to friends who are a long distance away. An example of this is a friend, unnamed, who is in Canada. She and I both enjoy memes and both enjoy Star Wars. I can communicate to her by sending a Star Wars related meme. She will often send a Star Wars related meme back. These memes on their own only relate to Star Wars, but by sending them to one another, we share opinions about the actual content of the Star Wars film. To elaborate, I send a meme that references to General Grievous trying to collect more lightsabers. This communicates to her that I am making a meme out of Grievous’s addiction to collecting lightsabers. While at the same time it is humorous, it comments on an odd feature of the character, which is understood by my Canadian friend. This communication, in short, allows us to converge onto a similar topic and relate to one another’s interest in Star Wars.

Communicating through memes is more than just communicating to people you know. Other observations I have noticed about the literacy involved with memes is also through the comment section. Almost every major social media has a comment section. To go into further detail about the comment section, I must mention that memes allow strangers to converse. An example of this is time I had a conversation under a Minecraft-related meme. The meme suggested, using humor, that a glowing squid would be useless in the game. I cannot directly quote the original conversation, but it went in a similar fashion.

Stranger: “To be honest, yeah, a glowing squid in Minecraft does not seem like a good idea.”

Me: “I am on the same page with you on that. I think the iceloger would have been a cool new mob in place of the glow squid.”

Stranger: “I wanted the moobloom. I think the iceloger would make it annoying to cross mountains. But I agree with you that anything would be more interesting than that glow squid.”

Me: “Still, the iceloger would have been another unique Illager to combat, but yeah, anything except the glow squid.”

This conversation, though brief, allowed a completely random person and me to talk about a game we both enjoy. This hinds at the fact that memes are capable of fostering communication. With the original message of the meme as the focal point, almost any topic can be explored, commented on, and discussed with others on the internet.

Memes only go to show how humans have evolved on the internet to maximize their need for a diverse way of communicating through humor, to be exact memes. Through the shared history of online memes, people can connect from great distances by relating to day-to-day humor. Today, my friends and I still share memes to keep in touch. We share memes that comment on our daily lives, what is going on in the news, and what our interests are. With that said, memes and literacy go hand in hand.

Works Cited

Adam. “Lord Marquaad E.” Know Your Meme , 2018, knowyourmeme.com/memes/lord-marquaad-e.

Blubber, Captain. “Trollface.” Know Your Meme , 2010, knowyourmeme.com/memes/trollface.

Blunt, James. “SpongeGar / Primitive Sponge / Caveman Spongebob.” Know Your Meme , 2015, knowyourmeme.com/memes/spongegar-primitive-sponge-caveman-spongebob.

Raspberry, Funky. “One Does Not Simply Walk into Mordor.” Know Your Meme ,2010, knowyourmeme.com/memes/one-does-not-simply-walk-into-mordor.

Understanding Literacy in Our Lives by Alexander Caldwell is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License , except where otherwise noted.

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Argumentative Essays About Social Media

This is a comprehensive resource to help you find the perfect social media essay topic. Whether you're navigating the complexities of digital communication, exploring the impact of social media on society, or examining its effects on personal identity, the right topic can transform your essay into a captivating and insightful exploration. Remember, selecting a topic that resonates with your personal interests and academic goals not only makes the writing process more enjoyable but also enriches your learning experience. Let's dive into a world of creativity and critical thinking!

Essay Types and Topics

Below, you'll find a curated list of essay topics organized by type. Each section includes diverse topics that touch on technology, society, personal growth, and academic interests, along with introduction and conclusion paragraph examples to get you started.

Argumentative Essays

Introduction Example: "In the digital age, social media platforms have become central to our daily interactions and self-perception, particularly among teenagers. This essay explores the impact of social media on teen self-esteem, arguing that while it offers a space for expression and connection, it also presents significant challenges to self-image. "

Conclusion Example: "Having delved into the complex relationship between social media and teen self-esteem, it is clear that the digital landscape holds profound effects on individual self-perception. This essay reaffirms the thesis that social media can both uplift and undermine teen self-esteem, calling for a balanced approach to digital engagement."

Introduction Example: "As political landscapes evolve, social media has emerged as a powerful tool for political mobilization and engagement. This essay investigates the role of social media in shaping political movements, positing that it significantly enhances communication and organizational capabilities, yet raises questions about information authenticity. "

Conclusion Example: "Through examining the dual facets of social media in political mobilization, the essay concludes that while social media is a pivotal tool for engagement, it necessitates critical scrutiny of information to ensure a well-informed public discourse."

Compare and Contrast Essays

Introduction Example: "In the competitive realm of digital marketing, Instagram and Twitter stand out as leading platforms for brand promotion. This essay compares and contrasts their effectiveness, revealing that each platform caters to unique marketing strengths due to its specific user engagement and content dissemination strategies. "

Conclusion Example: "The comparative analysis of Instagram and Twitter highlights distinct advantages for brands, with Instagram excelling in visual storytelling and Twitter in real-time engagement, underscoring the importance of strategic platform selection in digital marketing."

Descriptive Essays

Introduction Example: "Today's social media landscape is a vibrant tapestry of platforms, each contributing to the digital era's social fabric. This essay describes the characteristics and cultural significance of current social media trends, illustrating that they reflect and shape our societal values and interactions. "

Conclusion Example: "In portraying the dynamic and diverse nature of today's social media landscape, this essay underscores its role in molding contemporary cultural and social paradigms, inviting readers to reflect on their digital footprints."

Persuasive Essays

Introduction Example: "In an era where digital presence is ubiquitous, fostering positive social media habits is essential for mental and emotional well-being. This essay advocates for mindful social media use, arguing that intentional engagement can enhance our life experiences rather than detract from them. "

Conclusion Example: "This essay has championed the cause for positive social media habits, reinforcing the thesis that through mindful engagement, individuals can navigate the digital world in a way that promotes personal growth and well-being."

Narrative Essays

Introduction Example: "Embarking on a personal journey with social media has been both enlightening and challenging. This narrative essay delves into my experiences, highlighting how social media has influenced my perception of self and community. "

Conclusion Example: "Reflecting on my social media journey, this essay concludes that while it has significantly shaped my interactions and self-view, it has also offered invaluable lessons on connectivity and self-awareness, affirming the nuanced role of digital platforms in our lives."

Engagement and Creativity

As you explore these topics, remember to approach your essay with an open mind and creative spirit. The purpose of academic writing is not just to inform but to engage and provoke thought. Use this opportunity to delve deep into your topic, analyze different perspectives, and articulate your own insights.

Educational Value

Each essay type offers unique learning outcomes. Argumentative essays enhance your analytical thinking and ability to construct well-founded arguments. Compare and contrast essays develop your skills in identifying similarities and differences. Descriptive essays improve your ability to paint vivid pictures through words, while persuasive essays refine your ability to influence and convince. Finally, narrative essays offer a platform for personal expression and storytelling. Embrace these opportunities to grow academically and personally.

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Pros and Cons of Social Media: Social Networking

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The List of Pros and Cons of Social Media

The importance of staying safe on social media, impact of social media on our lives, social media: negative effects and addiction, discussion on whether is social media beneficial or harmful for society, negative effects of social media: relationships and communication, social media pros and cons, social media - good and bad sides, a study of the role of social media concerning confidentiality of personal data, how social media causes stereotyping, social media addiction: consequences and strategies for recovery, the role of social media in making us more narcissistic, the effect social media is having on today's society and political atmosphere, digital/social media, censorship in social media, why teenagers are addicted to social media and how it affects them, advantages and disadvantages of social media for society, enormous impact of mass media on children, the role of social media in the current business world, social media is the reason for many of the world’s problems and solutions.

Social media refers to dynamic online platforms that enable individuals to actively engage in the generation and dissemination of various forms of content, including information, ideas, and personal interests. These interactive digital channels foster virtual communities and networks, allowing users to connect, communicate, and express themselves. By harnessing the power of technology, social media platforms provide a space for individuals to share and exchange content, fostering connections and facilitating the flow of information in an increasingly digital world.

In a peculiar manner, the inception of social media can be traced back to May 24, 1844, when a sequence of electronic dots and dashes was manually tapped on a telegraph machine. Although the origins of digital communication have deep historical roots, most contemporary narratives regarding the modern beginnings of the internet and social media often point to the emergence of the Advanced Research Projects Agency Network (ARPANET) in 1969. The year 1987 witnessed the establishment of the direct precursor to today's internet, as the National Science Foundation introduced the more robust and expansive NSFNET, a nationwide digital network. A significant milestone occurred in 1997 when Six Degrees, the first genuine social media platform, was launched.

Mark Zuckerberg is a notable figure in the realm of social media as the co-founder and CEO of Facebook. Zuckerberg played a pivotal role in transforming Facebook from a small networking platform for college students into a global social media giant with billions of users. His innovative ideas and strategic decisions have reshaped the way people connect and share information online, making him one of the most influential individuals in the digital age. Jack Dorsey is recognized as one of the key pioneers of social media, notably for co-founding Twitter. Dorsey's creation revolutionized online communication by introducing the concept of microblogging, allowing users to share short messages in real-time. Twitter quickly gained popularity, becoming a powerful platform for news dissemination, public conversations, and social movements. Dorsey's entrepreneurial spirit and vision have contributed significantly to the evolution of social media and its impact on society. Sheryl Sandberg is a prominent figure in the social media landscape, known for her influential role as the Chief Operating Officer (COO) of Facebook.Sandberg played a crucial part in scaling and monetizing Facebook's operations, transforming it into a global advertising powerhouse. She is also recognized for her advocacy of women's empowerment and leadership in the tech industry, inspiring countless individuals and promoting diversity and inclusion within the social media sphere. Sandberg's contributions have left an indelible mark on the growth and development of social media platforms worldwide.

Social Networking Sites: Facebook, LinkedIn, and MySpace. Microblogging Platforms: Twitter. Media Sharing Networks: Instagram, YouTube, and Snapchat. Discussion Forums and Community-Based Platforms: Reddit and Quora. Blogging Platforms: WordPress and Blogger. Social Bookmarking and Content Curation Platforms: Pinterest and Flipboard. Messaging Apps: WhatsApp, Facebook Messenger, and WeChat.

Facebook (2004), Reddit (2005), Twitter (2006), Instagram (2010), Pinterest (2010), Snapchat (2011), TikTok (2016)

1. Increased Connectivity 2. Information Sharing and Awareness 3. Networking and Professional Opportunities 4. Creativity and Self-Expression 5. Supportive Communities and Causes

1. Privacy Concerns 2. Cyberbullying and Online Harassment 3. Information Overload and Misinformation 4. Time and Productivity Drain 5. Comparison and Self-Esteem Issues

The topic of social media holds significant importance for students as it plays a prominent role in their lives, both academically and socially. Social media platforms provide students with opportunities to connect, collaborate, and share knowledge with peers, expanding their learning networks beyond the confines of the classroom. It facilitates communication and access to educational resources, allowing students to stay updated on academic trends and research. Additionally, social media enhances digital literacy and prepares students for the realities of the digital age. However, it is crucial for students to develop critical thinking skills to navigate the potential pitfalls of social media, such as misinformation and online safety, ensuring a responsible and balanced use of these platforms.

The topic of social media is worthy of being explored in an essay due to its profound impact on various aspects of society. Writing an essay on social media allows for an in-depth examination of its influence on communication, relationships, information sharing, and societal dynamics. It offers an opportunity to analyze the advantages and disadvantages, exploring topics such as privacy, online identities, social activism, and the role of social media in shaping cultural norms. Additionally, studying social media enables a critical evaluation of its effects on mental health, politics, and business. By delving into this subject, one can gain a comprehensive understanding of the complex and ever-evolving digital landscape we inhabit.

1. Social media users spend an average of 2 hours and 25 minutes per day on social networking platforms. This amounts to over 7 years of an individual's lifetime spent on social media, highlighting its significant presence in our daily lives. 2. Instagram has over 1 billion monthly active users, with more than 500 million of them using the platform on a daily basis. 3. YouTube has over 2 billion logged-in monthly active users. On average, users spend over 1 billion hours watching YouTube videos every day, emphasizing the platform's extensive reach and the power of video content. 4. Social media has become a major news source, with 48% of people getting their news from social media platforms. This shift in news consumption highlights the role of social media in shaping public opinion and disseminating information in real-time. 5. Influencer marketing has grown exponentially, with 63% of marketers planning to increase their influencer marketing budget in the coming year. This showcases the effectiveness of influencers in reaching and engaging with target audiences, and the value brands place on leveraging social media personalities to promote their products or services.

1. Schober, M. F., Pasek, J., Guggenheim, L., Lampe, C., & Conrad, F. G. (2016). Social media analyses for social measurement. Public opinion quarterly, 80(1), 180-211. (https://academic.oup.com/poq/article-abstract/80/1/180/2593846) 2. Appel, G., Grewal, L., Hadi, R., & Stephen, A. T. (2020). The future of social media in marketing. Journal of the Academy of Marketing science, 48(1), 79-95. (https://link.springer.com/article/10.1007/s11747-019-00695-1?error=cookies_not_support) 3. Aichner, T., Grünfelder, M., Maurer, O., & Jegeni, D. (2021). Twenty-five years of social media: a review of social media applications and definitions from 1994 to 2019. Cyberpsychology, behavior, and social networking, 24(4), 215-222. (https://www.liebertpub.com/doi/full/10.1089/cyber.2020.0134) 4. Ruths, D., & Pfeffer, J. (2014). Social media for large studies of behavior. Science, 346(6213), 1063-1064. (https://www.science.org/doi/abs/10.1126/science.346.6213.1063) 5. Hou, Y., Xiong, D., Jiang, T., Song, L., & Wang, Q. (2019). Social media addiction: Its impact, mediation, and intervention. Cyberpsychology: Journal of psychosocial research on cyberspace, 13(1). (https://cyberpsychology.eu/article/view/11562) 6. Auxier, B., & Anderson, M. (2021). Social media use in 2021. Pew Research Center, 1, 1-4. (https://www.pewresearch.org/internet/wp-content/uploads/sites/9/2021/04/PI_2021.04.07_Social-Media-Use_FINAL.pdf) 7. Al-Samarraie, H., Bello, K. A., Alzahrani, A. I., Smith, A. P., & Emele, C. (2021). Young users' social media addiction: causes, consequences and preventions. Information Technology & People, 35(7), 2314-2343. (https://www.emerald.com/insight/content/doi/10.1108/ITP-11-2020-0753/full/html) 8. Bhargava, V. R., & Velasquez, M. (2021). Ethics of the attention economy: The problem of social media addiction. Business Ethics Quarterly, 31(3), 321-359. (https://www.cambridge.org/core/journals/business-ethics-quarterly/article/ethics-of-the-attention-economy-the-problem-of-social-mediaaddiction/1CC67609A12E9A912BB8A291FDFFE799)

Relevant topics

• Media Analysis
• Effects of Social Media
• Sociological Imagination
• American Identity
• Sex, Gender and Sexuality
• Discourse Community
• Social Justice
• Cultural Appropriation

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Argumentative Essay About Social Media : Topics, Tips & Examples

Are you struggling to come up with a topic for your argumentative essay about social media?

Don’t worry, you’re not alone.

With so many different opinions about social media, it can be difficult to know where to start. But fear not!

In this article, we’ll give you some tips on how to craft a great topic for your essay, as well as how to start your essay and some examples of argumentative essay topics about social media.

How to choose a topic for your argumentative social media essay

Choosing the right topic is the foundation of a successful argumentative essay . Here are some tips to help you choose the perfect topic for your social media essay:

• Identify the hot-button issues: Look for the topics that are currently generating the most attention and debate on social media. For instance, the issue of online privacy has been a hot-button issue for some time now.
• Analyze current events: Keep an eye on current events and trending topics on social media platforms. For example, the recent controversy surrounding Facebook’s role in the 2016 US Presidential election is an excellent topic to explore.
• Identify your audience: Consider the demographics of your audience, and choose a topic that will resonate with them. For instance, if you are writing for a younger audience, you may want to consider a topic related to the impact of social media on mental health.
• Personal experience: Consider your own experiences with social media and the impact it has had on your life. You may be able to identify a unique perspective that will make for a compelling argumentative essay.

How to craft a title for your argumentative essay about social media

Now that you know what topic you want to write on, let’s talk about how to craft a title that will grab your reader’s attention and accurately reflect your argument. Here are some tips:

• Use descriptive language: Your title should give your reader a good idea of what your essay is about. Use descriptive language that accurately reflects your argument. For example, if you’re writing about the advantages and disadvantages of social media, you might use a title like “Navigating the Pros and Cons of Social Media.”
• Keep it short and sweet: Your title should be concise and easy to remember. Avoid long titles that are difficult to read or remember. A good rule of thumb is to keep your title under 10 words.
• Make it provocative: A provocative title can grab your reader’s attention and make them want to read more. However, be careful not to be too sensationalistic or misleading. Your title should accurately reflect your argument.

Examples of Argumentative Essay Topics about Social Media

• Should social media platforms be held accountable for the spread of misinformation and fake news?
• The Social Dilemma: Navigating the Pros and Cons of Social Media
• Scrolling to Depression: The Impact of Social Media on Mental Health
• Fake News, Real Consequences: Holding Social Media Platforms Accountable
• Swipe Left on Toxic Relationships: The Impact of Social Media on Modern Dating
• The Future of Work in the Social Media Age: Opportunity or Threat?
• Hooked on Social Media: The Addictive Nature of Online Engagement
• Lost in Translation: How Social Media Affects Cross-Cultural Communication
• The Algorithms Behind the Screen: The Need for Transparency on Social Media Platforms
• Democracy in Danger? Examining the Impact of Social Media on Political Discourse
• Growing Up Online: The Impact of Social Media on the Development of Young Minds
• Is social media addiction a real problem, and if so, what steps should be taken to address it?
• Should social media companies be required to collect and store data about their users’ online activities?
• Are social media platforms responsible for the rise of cyberbullying and harassment, and what measures should be taken to prevent it?

How to Start an Argumentative Essay about Social Media

Starting an argumentative essay about social media can be a daunting task, but with the right approach, you can create a compelling and engaging introduction that hooks your reader’s attention. Here are some tips and examples to help you get started:

• Start with a hook that relates to your argument about social media
• Use a surprising statistic or fact: “Did you know that more than 60% of people have witnessed online harassment on social media platforms?”
• Use a provocative question: “Is social media a tool for positive social change or a threat to democracy?”
• Use a personal anecdote: “When I was in high school, I witnessed firsthand the negative impact of social media on my friend’s mental health.”
• Provide background information
• Define social media: “Social media refers to a variety of online platforms that allow users to share information, connect with others, and engage in social networking.”
• Explain the history of social media: “Social media has its roots in early online communities like Usenet and bulletin board systems, but it wasn’t until the rise of platforms like Facebook and Twitter that it became a mainstream phenomenon.”
• Outline the different types of social media: “There are a variety of social media platforms available, including social networking sites like Facebook and LinkedIn, microblogging sites like Twitter and Tumblr, and image-sharing sites like Instagram and Snapchat.”
• Present your thesis statement
• Focus on a specific aspect of social media: “While social media can be a useful tool for communication and entertainment, its addictive qualities and pressure to present a perfect image can have detrimental effects on mental health and well-being.”
• Take a stance: “Social media is a net positive for society, providing a platform for marginalized voices to be heard and allowing for greater social connection and community building.”
• Preview your main arguments: “In this essay, I will argue that social media is both a blessing and a curse, providing many benefits while also creating new challenges and problems that need to be addressed.”

How to Write the Body of a Social Media Argumentative Essay

The next section to write after the introduction is the body of your argumentative essay. Here are some tips on how to structure and write the body of your essay:

• Develop your arguments: In the body of your essay, you will need to develop the arguments that support your thesis statement. Each argument should be presented in a separate paragraph, and you should use evidence and examples to support your claims. For example, if you are arguing that social media has a negative impact on mental health, you could provide studies or articles that support your position.
• Address counterarguments: It is important to address counterarguments in your essay. This shows that you have considered different perspectives on the issue and strengthens your overall argument. For example, if you are arguing that social media has a negative impact on mental health, you could address the counterargument that social media can be a source of social support for some individuals.
• Use transitional phrases: Use transitional phrases to move smoothly from one argument to the next. This helps your essay to flow and makes it easier for your reader to follow your argument. Examples of transitional phrases include “in addition,” “moreover,” and “furthermore.”
• Provide a conclusion: Your conclusion should summarize your main arguments and restate your thesis statement. It should also provide some final thoughts or recommendations on the issue. Avoid introducing new information or arguments in your conclusion.

Example of an Argumentative Essay about Social Media

Title: Should social media platforms be held accountable for the spread of misinformation and fake news?

Did you know that your social media feed may be feeding you lies? In recent years, social media platforms have come under fire for their role in spreading fake news and misinformation. As more people turn to social media for their news and information, the potential impact of these falsehoods has become a growing concern. With debates raging about who should be held responsible for this spread of misinformation, this essay will argue that social media platforms must be held accountable for the consequences of the content they allow to spread. Social media has become a ubiquitous part of our daily lives, and with the increasing amount of information shared on these platforms, the potential for the spread of misinformation and fake news has become a significant concern. It is no longer a question of whether social media platforms should be held accountable for the spread of such content, but how they should be held accountable. Firstly, social media platforms must take responsibility for the accuracy and truthfulness of the content that is published on their platforms. Social media platforms are no longer mere conduits for information; they actively curate the content that is presented to users through algorithms and other tools (Allcott & Gentzkow, 2017). As such, they have the ability and the responsibility to ensure that the content that is presented to users is accurate and truthful. Social media platforms must be held accountable for any content that is found to be false, misleading or harmful to public health, safety, and well-being. Moreover, the impact of social media on public opinion and discourse cannot be understated. Studies have shown that the spread of fake news and misinformation can have a significant impact on public opinion and even influence election outcomes. As such, social media platforms have a responsibility to ensure that they are not facilitating the spread of false information that could influence important decision-making processes. They must ensure that their content policies and moderation practices are stringent enough to prevent the spread of harmful and false information. Some may argue that social media platforms should not be held accountable for the spread of misinformation and fake news as it can be difficult to determine what is true and false. However, this argument overlooks the fact that social media platforms have the resources and tools to combat the spread of false information(Allcott & Gentzkow, 2017). For example, these platforms can employ fact-checking mechanisms and algorithms that can detect false information and flag it for review. According to a study by Haim and Graefe (2018), social media platforms have the capability to implement these measures effectively. While it is true that detecting false information on social media platforms can be challenging, it is not an impossible task. In fact, social media platforms can improve their algorithms to better identify and flag false information. For instance, they can use machine learning and artificial intelligence to analyze patterns of behavior, source credibility, and language used to identify potentially false information. Moreover, social media platforms can collaborate with independent fact-checkers and news organizations to verify the accuracy of information before it is posted on their platforms (European Commission, 2018). By working with reputable sources, social media platforms can reduce the spread of misinformation and promote the sharing of accurate information. In conclusion, social media platforms should be held accountable for the spread of misinformation and fake news. As powerful gatekeepers of information, social media platforms have a responsibility to ensure that the content that is presented to users is accurate and truthful. They also have a legal obligation to remove illegal content, which may include false or misleading information. By taking these steps, social media platforms can help to mitigate the impact of misinformation and fake news on public opinion and discourse. References: Allcott, H., & Gentzkow, M. (2017). Social media and fake news in the 2016 election. Journal of Economic Perspectives, 31(2), 211-236. European Commission. (2018). Code of conduct on countering illegal hate speech online. Retrieved from https://ec.europa.eu/info/law/better-regulation/have-your-say/initiatives/11507-Code-of-conduct-on-countering-illegal-hate-speech-online-/public-feedback Haim, M., & Graefe, A. (2018). In a world of alternative facts, social media algorithms and crowdsourcing can help verify news. The Conversation. Retrieved from https://theconversation.com/in-a-world-of-alternative-facts-social-media-algorithms-and-crowdsourcing-can-help-verify-news-83503

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Argumentative Essay About Social Media

Crafting a Winning Argumentative Essay on Social Media

Published on: Feb 27, 2023

Last updated on: Jan 31, 2024

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Crafting a Powerful Argumentative Essay about Global Warming: A Step-by-Step Guide

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If you've ever gotten into an argument about social media, then you already know how important it is to craft a winning argument.

But what if that argument was turned into an essay?

Crafting an effective argumentative essay on social media can be both challenging and rewarding.

We'll show you everything you need to know in order to write a killer paper that takes your arguments straight to the top!

Read on for some tips and tricks on how to make sure your paper stands out among the rest.

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Argumentative Essay- Explained 

Before writing an argumentative essay about social media, it's important to understand what makes up a good argumentative essay. 

An argumentative essay is an article that presents both sides of an issue or debate in order to reach a conclusion. 

It requires you to provide evidence and facts, present a point of view, and develop an argument.

When writing an argumentative essay on social media, you must present both sides of the issue or debate in a balanced manner. 

You must also be sure to explain why one side has more credibility than the other. 

This means that you’ll need to do your research and make sure that your essay has facts and evidence to back up your claims. 

Why Do We Write an Argumentative Essay About Social Media?

This type of essay can be difficult because it requires you to present both sides of the argument in a balanced and unbiased manner. 

It also requires you to research facts that support either side of the argument and present them in a clear and logical manner.

By writing this essay, you can help readers understand why one point of view is more credible than another. 

This can help them form their own opinions on the issue and become better informed on the topic. 

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Steps to Write an Argumentative Essay About Social Media

Writing an argumentative essay about social media requires research, facts, and evidence. 

Here are a few steps that can help you write a great argumentative essay:

Research To Collect Data and Material 

The first step in writing an argumentative essay about social media is to do research and collect data .

This includes researching various sources such as books, articles, and websites that provide reliable information about the topic. 

Take notes on what you read and highlight any points or quotes that you may want to include in your essay. 

Pick an Engaging Title for an Argumentative Essay About Social Media 

When it comes to writing a great argumentative essay about social media, one of the most important elements is having a great title. 

A good title will draw readers in and encourage them to read your essay.

Make sure the title is catchy yet relevant to the main topic of your paper. 

Form a Descriptive Outline 

Once you have collected enough data and material, it’s time to start forming a descriptive outline of your essay. 

This should include all the points you plan on discussing throughout the body paragraphs. Furthermore, it should include any conclusions that you may want to propose at the end of your paper. 

By having a clear idea of what your paper will cover, it will be much easier to plan out each section before writing it out in full detail.

Check out this amazing blog on argumentative essay outline to craft perfect outlines.

Write an Introduction of an Argumentative Essay About Social Media 

Your introduction should be engaging and introduce readers to the main topic of your paper.

Here, you can also state which side of the argument you are taking (if applicable) so readers know where you stand from the beginning. 

Write Connect The Body Paragraphs Of Your Essay  

In each body paragraph, provide evidence or facts that prove why your opinion is correct.

Each paragraph should introduce a new point or idea related back to your main argument.

Make sure each point flows naturally into one another without jumping around too much from one point/idea to another.  

Write A Compelling Conclusion                  

Finally, write a compelling conclusion that wraps up all points made throughout the body paragraphs.  

Make sure not only summarize what was already said. Also, provide insight into why these topics are still relevant today and how they affect us today going forward!  

Examples of Argumentative Essay About Social Media 

When writing an argumentative essay about social media, it can be helpful to look at examples.

Here is a sample argumentative essay written by our expert writers. Check it out for more inspiration.

By reading these sample essays, you can gain a better understanding of how to write your own essay and what elements are important to include. 

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Check our extensive blog on argumentative essay examples to ace your next essay!

Argumentative Essay About Social Media Topics

If you’re looking for topics to write about in your argumentative essay about social media, take a look at the list below for some ideas: 

• The Impact of Social Media on Human Interaction 
• How Can We Limit Social Media Use? 
• Is Social Media Harmful/Beneficial to Mental Health? 
• Social Media and Its Effect on the Education System 
• Is Social Media Really a Positive Influence on Young People? 
• The Impact of Social Media on Privacy 
• How Has Social Media Changed Society in Recent Years? 
• Should We Censor Content Posted on Social Media Platforms like Twitter and Facebook? 
• Does Social Media Make Us Feel More Alone? 
• Are Social Media Users Becoming Increasingly Narcissistic? 
• Should We Rely on Social Media for News Sources? 
• Is Social Media a Tool of Surveillance? 

Check our comprehensive blog on argumentative essay topics to get more topic ideas!

The platform that you use to communicate with others can be a great tool or it can do more harm than good. It all depends on how you use it and what your intentions are. 

You can find social media argumentative essay examples all over the internet, but not every one of them is going to be a winner. 

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Argumentative Essay on Social Media

Introduction

In the modern era, the surge of social networks is virtually irresistible, enveloping society in a cocoon of interconnected digital networks. An argumentative essay about social media often dives into this complex web, exploring the multifaceted issues interwoven with online platforms. This essay will navigate through the controversial sea of social media, underscoring its positive and negative impacts on society.

Formulating the Problem

Social media, as an accessible platform for individuals of various ages and backgrounds, brings about not just advantages like global connectivity and information dissemination, but also palpable challenges such as privacy invasion, cyberbullying, and misinformation spread. The core issue here is discerning whether the benefits of social media outweigh its drawbacks, essentially necessitating an exploration of various social media argumentative essay examples to delineate comprehensive insights.

Commentary on the Problem

The extensive reach and influence of social media indisputably carve both constructive and destructive pathways in society. Examples of the latter include the rampant dissemination of fake news, fostering polarization, and impairing interpersonal relationships with the illusion of connectedness, all of which feed into the intricacies of an argumentative essay on social media . Conversely, the positive aspects, like enhanced communication, awareness, and a platform for social change, cannot be discounted.

Author’s Position

This essay posits that while social media harbours potential for immense societal benefit, its perils, if left unchecked and unregulated, could overshadow its positives. Consequently, an argumentative stance herein insists on meticulous regulatory frameworks and educational initiatives to safeguard users while maximizing the platform's advantageous elements.

Agreement/Disagreement and Argumentation

• Promotion of Information and Awareness: Social media notably excels in swiftly disseminating information on a global scale, enabling users to remain abreast of worldwide occurrences and innovations.

Disagreement:

• Psychological Impact: Various social media argumentative essay sources highlight its psychological impacts, including anxiety and depression, attributed to online harassment and the perpetuation of unrealistic standards.
• Misinformation: Argument essay about social media often spotlight the proliferation of misinformation as a pressing concern. False data and fake news can propagate rapidly, fueling discord, panic, and uninformed decision-making among users.
• Privacy Concerns: Social media argument essay narratives frequently underline the incessant erosion of user privacy, with personal data often being misused for profit or manipulative endeavors.

Social media stands at a juxtaposition of being a boon and a bane, intricately entwining diverse global narratives, making the topic a compelling subject for an argumentative essay social media . Despite the numerous advantages it presents, the detriments of social media cannot be understated or ignored. Striking a balance through regulatory frameworks, digital literacy, and ethical usage is imperative to harness its potential effectively while mitigating associated risks.

1. Ice Bucket Challenge: A Beacon of Positive Potential

In 2014, the Ice Bucket Challenge became an exemplar of how social media can serve as a vessel for widespread positivity, charitable action, and education on global health issues. By challenging individuals to pour a bucket of iced water over themselves and subsequently nominate others to do the same or donate to ALS research, it ingeniously melded entertainment, camaraderie, and philanthropy. With celebrities and common folk alike participating, the challenge not only raised an astonishing $115 million for ALS research in the United States but also significantly enhanced global awareness regarding the disease. Here, social media manifested as a formidable force for good, underlining its potential to elevate charitable causes and promote global solidarity.

2. Pizzagate Conspiracy Theory: Navigating through the Abyss of Misinformation

Conversely, the Pizzagate Conspiracy Theory provides a grim glimpse into the detrimental potentials of social media when pervaded by misinformation. Emerging during the 2016 United States presidential election, the theory falsely claimed that a Washington D.C. pizzeria was the nexus of a child-trafficking ring, allegedly linked to high-profile politicians. Propagated through social media channels, it not only sowed seeds of distrust towards democratic institutions and individuals but also resulted in a perilous real-world incident, wherein an armed individual sought to 'investigate' the matter, endangering lives. This highlights an exigent need to combat the unchecked dissemination of misinformation and the pivotal role of regulatory and educative interventions in mitigating such instances.

3. Rise of Influencer Culture: Redefining Marketing and Consumer Behavior

The ascension of influencer culture exemplifies another intriguing dimension of social media. With platforms such as Instagram and TikTok spearheading a new age of marketing, influencers have become pivotal in shaping consumer behavior, lifestyle choices, and brand preferences among followers. While this has democratized fame and offered new avenues for business and individuals to prosper, it also beckons a scrutiny of ethical marketing, the impact of materialistic pursuits, and the psychological implications among followers, especially younger audiences, ensuing from continuous exposure to curated and often, unrealistic portrayals of life and success.

In threading through the variegated aspects of social media, this essay endeavours to prompt reflection, advocating for a nuanced approach to its utilization and regulation. This not only ensures its optimal use but also safeguards the mental and societal health of its vast user base.

Note: This essay is a general guideline and should be expanded upon for a detailed, comprehensive exploration of the topic. It offers a structured overview and can be enhanced with specific details, data, and further discussions per section.

Frequently Asked Questions

• How can an argumentative essay about social media address the psychological impacts on users?

Answer: An argumentative essay might explore the psychological repercussions by diving into various studies and real-life incidents, illustrating the stark realities and cascading effects of social media on mental health.

• What role does misinformation play in the framework of a social media argumentative essay?

Answer: Misinformation takes a central role in a social media argumentative essay, highlighting how false narratives and deceptive information can distort public opinion, endanger public health, and even compromise the integrity of democracies.

• How does an argumentative essay on social media evaluate the platform’s potential as a tool for social justice and change?

Answer: The essay could dissect several instances, such as social movements and campaigns that have leveraged social media for visibility and mobilization, exploring its viability and limitations as a conduit for social transformation.

• In what way does an argumentative essay social media delve into the aspects of privacy invasion and data misuse?

Answer: The essay might scrutinize numerous instances of data breaches and the exploitation of personal information, weaving a narrative that elucidates the gravity and breadth of privacy issues spawned by social media platforms.

• Can you cite a few social media argumentative essay examples that illuminate both the positive and negative facets of these platforms?

Answer: Certainly, essays might focus on varied instances like the global connectivity during the COVID-19 pandemic, amplifying social causes like Black Lives Matter, or delve into the darker facets like the Cambridge Analytica scandal and widespread cyberbullying, offering a multi-dimensional viewpoint on the spectrum of impacts rendered by social media.

These questions and the entailing discussions are pivotal, embodying the core of numerous debates surrounding social media and its varied implications on contemporary society. They underscore not just its evident advantages but also the covert, often insidious repercussions that necessitate astute scrutiny and deliberation, aspects crucial to any compelling argumentative essay social media.

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Comparative Analysis Essay Topics in Education

Delving into comparative analysis essays in education challenges us to dissect and debate pivotal learning themes. Our carefully selected "Top 20 Topics, Prompts, Ideas, and Questions" aim to ignite critical thought, pushing you to evaluate and contrast varied educational frameworks and the efficacy of instructional approaches. In drafting your essay, strive for a cohesive argument that elevates your analysis beyond the obvious. These topics are springboards for broader discussion, offering a l

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Ethical decision-making is the process of choosing between various options, where the choices are guided by ethical principles and values. This essay explores the foundational rules of ethical decision-making, the possible and ideal ground rules, the implications of such decisions, and the application of a personal ethical framework to a difficult decision in my life. We will delve into the significance of ethics in decision-making processes and speculate on potential improvements for the future

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300 Questions and Images to Inspire Argument Writing

Recent Student Opinion and Picture Prompts, categorized by topic, to help students discover the issues that matter to them.

By The Learning Network

Update: This list is available as a PDF .

If you’ve taught argument writing with our resources in the past, you already know we ask a fresh question every day as part of our long-running Student Opinion series . Teenagers around the world are invited to visit and post their thoughts on topics including politics, medical ethics, fashion, sports and entertainment.

We’ve rounded up lists of these prompts in the past, but this year we’re doing something new: Below you can find a categorized collection of all our recent, relevant Student Opinion questions, but alongside them we’re also including related Picture Prompts. These short, image-based forums are accessible to learners of all ages, but still provide engaging jumping-off points to help students make and support claims.

For instance, let’s say your class is interested in meme culture. A Student Opinion question asks, “ Do Memes Make the Internet a Better Place? ” and invites students to read and weigh in on a New York Times article that examines the role of memes in how teenagers process world events. Over 700 students have already submitted their thoughts .

But if you scan the “Technology and Social Media” category below, you’ll see we also have a Picture Prompt that asks a more direct, concrete question: “ What are your favorite memes? ” For many, that may be a fun, comfortable place to start.

So give your students both “voice and choice” by inviting them to find the questions and format that speak to them. All the prompts below are still open for comment. We look forward to seeing which ones inspire the most passionate arguments, and we invite your class to submit the results to our Eighth Annual Editorial Contest .

Argumentative Prompt Topics

Technology & social media, coronavirus, college & career, mental & physical health, race & gender, parenting & childhood, ethics & morality, government & politics, other questions.

Article-Based Prompts

1. How Worried Should We Be About Screen Time During the Pandemic? 2. How Do You Feel About Cancel Culture? 3. Do Memes Make the Internet a Better Place? 4. Does Online Public Shaming Prevent Us From Being Able to Grow and Change? 5. How Young Is Too Young to Use Social Media? 6. Where Should We Draw the Line Between Community Health and Safety and Individual Liberty and Privacy? 7. Do You Think Online Conspiracy Theories Can Be Dangerous? 8. What Do You Think of the Decision by Tech Companies to Block President Trump? 9. Should the Adults in Your Life Be Worried by How Much You Use Your Phone? 10. Is Your Phone Love Hurting Your Relationships? 11. Do You Trust Facebook? 12. Do You Think Recreational Drones Are Safe? 13. Should Kids Be Social Media Influencers? 14. Does Grammar Still Matter in the Age of Twitter? 15. Should Texting While Driving Be Treated Like Drunken Driving? 16. How Do You Think Technology Affects Dating?

Image-Based Prompts

17. Online Video Games : Does more need to be done to make online gaming communities safer? 18. A Computer in Everything : Do “smart” devices worry you? 19. Snail Mail : Do you think handwritten cards and letters still have value in the digital age? 20. Cyberbullying : Should social media companies do more to prevent online harassment? 21. Phone Manners : Are there times when you think using your phone while you’re with other people is rude? 22. Alarm Clocks : Are there any “dumb” devices that you think are better than “smart” devices? 23. Phone Warnings : Should tech devices come with addiction advisories? 24. Phones in Church : Are there some places where phones just don’t belong? 25. Driverless Cars : What do you think about driverless cars? 26. Texting While Walking : Should looking at your phone while crossing the street be illegal? 27. Device Addiction? : As a society, are we too addicted to our devices? 28. ‘A Man Needs His Nuggs’ : What do you think of Carter Wilkerson’s quest, and its results? 29. Soothing Video Games : Can video games intended to calm the mind be fun? Worthwhile? 30. Our Lives on Social Media : How much do you think we can judge our collective happiness by what is posted on social media? 31. ‘Bracelet of Silence’ : Would you wear privacy armor? 32. Baby Yoda : What are your favorite memes? 33. Tesla’s ‘Cybertruck’ : What do you think of this “pickup of the future”? 34. The ‘Bird Box’ Challenge : What do you think of social media challenges like this one?

35. Should Media Literacy Be a Required Course in School? 36. Should Schools Be Able to Discipline Students for What They Say on Social Media? 37. How Should Schools Hold Students Accountable for Hurting Others? 38. Should Schools Provide Free Pads and Tampons? 39. Can Empathy Be Taught? Should Schools Try to Help Us Feel One Another’s Pain? 40. When the Pandemic Ends, Will School Change Forever? 41. Should Schools Change How They Grade Students During the Pandemic? 42. Should Students Be Monitored When Taking Online Tests? 43. Should There Still Be Snow Days? 44. How Should Racial Slurs in Literature Be Handled in the Classroom? 45. Should Teachers Be Allowed to Wear Political Symbols? 46. Should Schools or Employers Be Allowed to Tell People How They Should Wear Their Hair? 47. Are Straight A’s Always a Good Thing? 48. Should Schools Teach You How to Be Happy? 49. How Do You Think American Education Could Be Improved? 50. Should Schools Test Their Students for Nicotine and Drug Use? 51. Can Social Media Be a Tool for Learning and Growth in Schools? 52. Should Facial Recognition Technology Be Used in Schools? 53. Should Your School Day Start Later? 54. Should Yearbooks Include Political News? 55. How Should Senior Year in High School Be Spent? 56. Should Teachers Be Armed With Guns? 57. Is School a Place for Self-Expression? 58. Should Students Be Punished for Not Having Lunch Money? 59. Is Live-Streaming Classrooms a Good Idea? 60. Should Gifted and Talented Education Be Eliminated? 61. What Are the Most Important Things Students Should Learn in School? 62. Should Schools Be Allowed to Censor Student Newspapers? 63. Do You Feel Your School and Teachers Welcome Both Conservative and Liberal Points of View? 64. Should Teachers and Professors Ban Student Use of Laptops in Class? 65. Should Schools Teach About Climate Change? 66. Should All Schools Offer Music Programs? 67. Does Your School Need More Money? 68. Should All Schools Teach Cursive? 69. What Role Should Textbooks Play in Education? 70. Do Kids Need Recess? 71. Should Public Preschool Be a Right for All Children?

72. Graduation in a Pandemic : Is your school doing enough to honor seniors? 73. Most Challenged Books : Are there books that don’t belong in schools or public libraries? 74. Mascot : If you could choose one mascot to represent your school, what would it be? 75. Math : How do you feel about math? 76. Sleep Deprivation : Do you think school should start later for teenagers? 77. Standardized Tests : Is there too much testing at your school? Why or why not? 78. Teacher Walkouts : Do you think teachers should be paid more? Why or why not? 79. Mermaid School : If there could be a special school that would teach you something you really want to learn, what would that school be?

Article-Based Prompts 80. What Weaknesses and Strengths About Our World Are Being Exposed by This Pandemic? 81. As Coronavirus Cases Surge, How Should Leaders Decide What Stays Open and What Closes? 82. How Should We Balance Safety and Urgency in Developing a Covid-19 Vaccine? 83. Do You Want Your Parents and Grandparents to Get the New Coronavirus Vaccine? 84. Do You Think People Have Gotten Too Relaxed About Covid? 85. How Do You Feel About Mask-Slipping?

86. Surge : How should the United States keep the coronavirus pandemic at bay? 87. Masks : What “civic rules” do you think we should all follow now? 88. Paid to Laugh : Would you attend a live TV show taping — if you got money for it? 89. Dolly’s Donation : How do you feel about celebrity philanthropy? 90. Crowds and Covid : How do you feel about crowds during the pandemic? 91. Going Nowhere Fast : Would you take a flight to nowhere?

92. Should Students Be Required to Take the SAT and ACT to Apply to College? 93. Should National Service Be Required for All Young Americans? 94. What Is Your Reaction to the College Admissions Cheating Scandal? 95. Is the College Admissions Process Fair? 96. Should Everyone Go to College? 97. Should College Be Free? 98. Are Lavish Amenities on College Campuses Useful or Frivolous? 99. Should ‘Despised Dissenters’ Be Allowed to Speak on College Campuses? 100. How Should the Problem of Sexual Assault on Campuses Be Addressed? 101. Should Fraternities Be Abolished? 102. Is Student Debt Worth It? 103. Do Other People Care Too Much About Your Post-High School Plans? 104. Should All Young People Learn How to Invest in the Stock Market?

105. Jack-of-All-Trades : Is it better to focus on one thing early in life and get really good at it?

106. Should Students Get Mental Health Days Off From School? 107. Is Struggle Essential to Happiness? 108. Does Every Country Need a ‘Loneliness Minister’? 109. Should Schools Teach Mindfulness? 110. Should All Children Be Vaccinated? 111. What Do You Think About Vegetarianism? 112. Do We Worry Too Much About Germs? 113. What Advice Should Parents and Counselors Give Teenagers About Sexting? 114. Are Emotional-Support Animals a Scam? 115. Do You Believe in Manifesting?

116. Optimism : Is your glass half-empty or half-full? 117. Cursing : Is it ever OK, useful or even healthy to curse? Or is it always inappropriate? 118. Anger Rooms : Do you think places like this are a good idea?

119. What Is Your Reaction to the Days of Protest That Followed the Death of George Floyd? 120. How Should Parents Teach Their Children About Race and Racism? 121. Is America ‘Backsliding’ on Race? 122. Should All Americans Receive Anti-Bias Education? 123. Should All Companies Require Anti-Bias Training for Employees? 124. Should Columbus Day Be Replaced With Indigenous Peoples Day? 125. Is Fear of ‘The Other’ Poisoning Public Life? 126. Justice Ginsburg Fought for Gender Equality. How Close Are We to Achieving That Goal? 127. What Should #MeToo Mean for Teenage Boys? 128. Should There Be More Boy Dolls? 129. Should the Boy Scouts Be Coed? 130. What Is Hard About Being a Boy?

131. Fashion-Show Diversity : What other industries or aspects of life need more diversity? 132. A Town’s New Seal : Why do you think Whitesboro, N.Y., decided to change its seal? 133. Gender Expectations : Do you ever find gender expectations or norms confining? 134. Women’s History Month : What does this holiday mean to you? 135. Boys and Men : What does it mean to “be a man”? 136. Women in Movies : Should some movies dominated by male actors be remade with largely female casts? 137. Unisex Clothing : Should clothing labeling be unisex? 138. Feminism : Do you consider yourself a feminist? 139. Gender and ‘Genderless’ : Do you think that gender is binary?

140. What Are the Greatest Songs of All Time? 141. Should Museums Return Looted Artifacts to Their Countries of Origin? 142. How Do You Feel About Censored Music? 143. What Role Should Celebrities Have During the Coronavirus Crisis? 144. Can You Separate Art From the Artist? 145. Are There Subjects That Should Be Off-Limits to Artists, or to Certain Artists in Particular? 146. Should Art Come With Trigger Warnings? 147. Should Graffiti Be Protected? 148. Is the Digital Era Improving or Ruining the Experience of Art? 149. Are Museums Still Important in the Digital Age? 150. In the Age of Digital Streaming, Are Movie Theaters Still Relevant? 151. Is Hollywood Becoming More Diverse? 152. What Stereotypical Characters Make You Cringe? 153. Do We Need More Female Superheroes? 154. Do Video Games Deserve the Bad Rap They Often Get? 155. Should Musicians Be Allowed to Copy or Borrow From Other Artists? 156. Is Listening to a Book Just as Good as Reading It? 157. Is There Any Benefit to Reading Books You Hate?

158. Hologram Musicians : Which departed artists would you like to see perform live? 159. Movie Theaters : In the age of digital streaming, are movie theaters still relevant? 160. ‘The Image of the Revolution’ : What is it about this photograph that makes it so powerful? 161. Book Covers : What are your favorite book covers? Why? 162. Fashion Trends : What are your favorite fashion trends? What trends do you hate? 163. Fashion Comebacks : What trends from the past would you like to see revived? 164. Murals : Can art be an act of resistance? 165. An 18-Karat Throne : Is this art? 166. A Hug Seen Around the World : Why do you think this image became so popular so quickly? 167. The Role of Public Broadcasting : Do you think programs like “Sesame Street” make the U.S. smarter, stronger and safer? 168. Best Books? : What have you read and loved this year?

169. Should Girls and Boys Sports Teams Compete in the Same League? 170. Should College Athletes Be Paid? 171. Are Youth Sports Too Competitive? 172. Is It Selfish to Pursue Risky Sports Like Extreme Mountain Climbing? 173. How Should We Punish Sports Cheaters? 174. Should Technology in Sports Be Limited? 175. Should Blowouts Be Allowed in Youth Sports? 176. Are Some Youth Sports Too Intense? 177. Does Better Sports Equipment Unfairly Improve Athletic Ability? 178. Is It Offensive for Sports Teams and Their Fans to Use Native American Names, Imagery and Gestures?

179. Brady’s Big Move : How do you feel about Tom Brady leaving the Patriots? 180. Tiger Woods Wins : What are the greatest comebacks in history? 181. Referees : Do sports officials deserve more respect? 182. $430 Million Deal : Is any athlete worth that amount of money? 183. Super Bowl Commercials : Was it smart for advertisers to steer clear of controversy in 2019? 184. Champions : What team in any sport would you like to see win a championship? 185. The Outspoken N.B.A. : Should all sports leagues treat political speech as a right for their players? 186. Gymnastics on Horseback : What is the world’s most difficult sport? 187. Tackle Football : Should children under the age of 12 play tackle football, in your opinion? 188. Breakdancing : Should dance be an Olympic event? 189. Coed Sports : Do you think women and men should compete against each other in sports? 190. Super Bowl Halftime Performer : Whom would you choose to perform at the Super Bowl, and why? 191. Colin Kaepernick’s Protest : What do you think of this protest?

192. Should Parents Track Their Children? 193. Who Should Decide Whether a Teenager Can Get a Tattoo or Piercing? 194. Is It Harder to Grow Up in the 21st Century Than It Was in the Past? 195. Is Childhood Today Over-Supervised? 196. How Should Parents Talk to Their Children About Drugs? 197. What Should We Call Your Generation? 198. Do Parents Ever Cross a Line by Helping Too Much With Schoolwork? 199. What’s the Best Way to Discipline Children? 200. What Are Your Thoughts on ‘Snowplow Parents’? 201. Should Stay-at-Home Parents Be Paid? 202. When Do You Become an Adult?

203. Household Chores : Do you think children should help out around the house? 204. Spy Cams : Should parents use smart devices to keep tabs on their children when they’re home alone? 205. Adults With Rainbow Hair : Are there some trends adults just should not try? 206. Parenting Skills : Should parents say “no” more often when their children ask for new things?

207. Should Students Be Monitored When Taking Online Tests? 208. What Makes a Great Leader? 209. Is It OK to Laugh During Dark Times? 210. Is It Immoral to Increase the Price of Goods During a Crisis? 211. Would You Allow an Ex-Prisoner to Live With You? 212. Would You Return a Lost Wallet? (What if It Had Lots of Money in It?) 213. Is It Wrong to Focus on Animal Welfare When Humans Are Suffering? 214. Is Animal Testing Ever Justified? 215. Should We Be Concerned With Where We Get Our Pets? 216. Is This Exhibit Animal Cruelty or Art? 217. Should Extinct Animals Be Resurrected? If So, Which Ones? 218. Why Do Bystanders Sometimes Fail to Help When They See Someone in Danger? 219. Is It Ethical to Create Genetically Edited Humans? 220. Should Reporters Ever Help the People They Are Covering? 221. Is It OK to Use Family Connections to Get a Job? 222. Is $1 Billion Too Much Money for Any One Person to Have? 223. Are We Being Bad Citizens If We Don’t Keep Up With the News? 224. Should Prisons Offer Incarcerated People Education Opportunities? 225. Should Law Enforcement Be Able to Use DNA Data From Genealogy Websites for Criminal Investigations? 226. Should We Treat Robots Like People?

227. World’s Big Sleep Out : What lengths would you go to in support of a worthy cause? 228. Tipping : Do you leave a tip whenever you’re asked to? 229. Cash Reward : Should you accept a cash reward for doing the right thing? 230. Cheating : Would you tell if you caught your classmates cheating? 231. Do Not Resuscitate : Should doctors have tried to revive this man? 232. Hitler and History : Should the bunker where Hitler killed himself be a tourist attraction? 233. Solving Global Problems : As the head of a global foundation, what problem would you solve?

234. Should the Death Penalty Be Abolished? 235. If You Were a Member of Congress, Would You Vote to Impeach President Trump? 236. Who Do You Think Should Be Person of the Year for 2020? 237. Should the United States Decriminalize the Possession of Drugs? 238. What Would You Do First if You Were the New President? 239. Does Everyone Have a Responsibility to Vote? 240. How Should We Remember the Problematic Actions of the Nation’s Founders? 241. Do You Care Who Sits on the Supreme Court? Should We Care? 242. Is the Electoral College a Problem? Does It Need to Be Fixed? 243. Are Presidential Debates Helpful to Voters? Or Should They Be Scrapped? 244. Is Your Generation Doing Its Part to Strengthen Our Democracy? 245. Should We All Be Able to Vote by Mail? 246. What Issues in the 2020 Presidential Race Are Most Important to You? 247. Do You Think the American Dream Is Real? 248. Should Plastic Bags Be Banned Everywhere? 249. Does the United States Owe Reparations to the Descendants of Enslaved People? 250. Do You Think It Is Important for Teenagers to Participate in Political Activism? 251. Should the Voting Age Be Lowered to 16? 252. What Should Lawmakers Do About Guns and Gun Violence? 253. Should Confederate Statues Be Removed or Remain in Place? 254. Does the U.S. Constitution Need an Equal Rights Amendment? 255. Should National Monuments Be Protected by the Government? 256. Should Free Speech Protections Include Self Expression That Discriminates? 257. How Important Is Freedom of the Press? 258. Should Ex-Felons Have the Right to Vote? 259. Should Marijuana Be Legal? 260. Should the United States Abolish Daylight Saving Time? 261. Should the U.S. Ban Military-Style Semiautomatic Weapons? 262. Should the U.S. Get Rid of the Electoral College? 263. What Do You Think of President Trump’s Use of Twitter? 264. Should Celebrities Weigh In on Politics? 265. Why Is It Important for People With Different Political Beliefs to Talk to Each Other? 266. Should Athletes Speak Out On Social and Political Issues?

267. Government Buildings : Should they all look like the Lincoln Memorial? 268. Oprah for President : Would you vote for her if you could? 269. Peaceful Protesting : In what ways can you demonstrate peacefully to express your views? 270. Student Climate Strikes : What issues do you think deserve more attention? 271. Pennies : Should the United States get rid of the penny? 272. Mandatory Voting? : Should citizens who are 18 or older be required to vote? 273. Dabbing in Congress : Should this teenager have dabbed in his father’s official swearing-in photo? 274. Baby Bonds : Should the government give money to babies?

275. We Document Life’s Milestones. How Should We Document Death? 276. Does Reality TV Deserve Its Bad Rap? 277. Do Marriage Proposals Still Have a Place in Today’s Society? 278. Should We Rethink Thanksgiving? 279. How Do You Decide What News to Believe, What to Question and What to Dismiss? 280. Should the Week Be Four Days Instead of Five? 281. Should Public Transit Be Free? 282. How Important Is Knowing a Foreign Language? 283. Is There a ‘Right Way’ to Be a Tourist? 284. Should Your Significant Other Be Your Best Friend? 285. What Do You Think of the #WalkUpNotOut Movement?

286. Teenage Drivers : What do you think of Georgia’s decision to issue driver’s licenses without road tests? 287. Snow Days : How do you feel about winter weather? 288. Fortune Tellers : Do you believe in psychics? 289. Big City, Small Town : Which would you rather live in? Why? 290. Game Show Winner : Would you ever want to be a contestant on a game show? 291. Fast-Food Buffet : Is this the feast of your dreams or your nightmares? 292. Public Libraries : Are libraries still relevant and important today? 293. Trans Fats : Should trans fats be banned around the world? 294. Dolls : If you could have your favorite toy company make a doll of someone, who would it be and why? 295. Creepy Clowns : How do you feel about clowns? 296. Tattoos : How do you feel about tattooing in general? 297. Brushing Beagle : What are the best dog breeds, in your opinion? 298. U.F.O.s : Do you believe that U.F.O.s are signs of alien life? 299. Small Talk : Do you have the gift of gab? 300. Lottery Winnings : Would you want to win the lottery? Why or why not?

• Social Issues

Argumentative Essay on Social Media

Today our world is full of a whole lot of opinionated people. Everyone loves to share what they think about almost any topic. Whether the topic is very important or completely irrelevant. Although everyone has opinions on things that are somewhat unimportant, some topics are worth discussing our opinions on. One of which that most definitely has some of the most diverse opinions on is social media. Many people think that social media is distracting, negative, and harmful, while others think it is one of the best things that has ever happened and are addicted to it. Some people love to scroll through Instagram or talk to people on Snapchat; However, they still think that the majority of the time social media is much more harmful than helpful. While Social media can provide a place to catch up with friends and things going on in the world, it also has the ability to completely tear lives apart and in some cases lead to depression or anxiety. People with social media should limit their time on these apps or even in some cases, delete the apps altogether due to the negative effects and all of the drama. 

How It Really Is

In contrast to what some people think, Social media is far more harmful than helpful. There are numerous reasons as to why social media is harmful, to start with, there is entirely too much drama and false information that spreads quickly all over social media apps. As a result of this, a whole lot of people are substantially more unhappy with themselves and with their lives. In some cases, social media is even likely to encourage people to do things they should not do and will regret later on in their lives. 

One example of this could be whenever somebody is bullying someone through Instagram and the pressure of being like everyone else could possibly make someone go along with it just because everyone else is doing it. Although a great deal of people claim they would never bully anyone, it is surprising how quickly social media can change a person and cause them to do things they wouldn’t expect to ever do. In the article “Social media websites can harm and help kids” by Nanci Hellmich, she states that “Facebook and other social media websites can enrich children’s lives, but they could also be hazardous to their mental and physical health” (Hellmich). 

This statement is completely agreeable because at first social media can be fun, but eventually it can become addictive and affect people negatively without them even realizing it. In quite a few instances, social media gets so awful to the point where people should delete it, however, it can be remarkably addicting, so people want to stay on it just to continue to see the drama and negative things happening instead of simply deleting the apps.

Not only does social media cause unhappiness and even depression in some cases, it can also be extremely distracting. For many people, social media is the most distracting out of everything in their lives. Not only does it prevent several important things, like doing chores or homework, it can even prevent spending time with friends and family, or even getting enough sleep at night. To start out, being on social media is mostly fun, however, the more time spent on it the more it gets to the point of taking over a tremendous part of people's lives. One example of this being a distraction is stated in the article “Social Networking: Helpful or Harmful”, “A lot of my friends and I spend a lot of time on Facebook, and it is often a big distraction from our work.” (Winkler), This is one of the various instances of somebody being distracted by and affected negatively by social media apps. This shows that social media being distracting is a problem many people with the apps face. 

Social media is quite a controversial topic in the world today. Some people believe it truly does have a negative impact on the world, while others may argue that social media is very entertaining and allows an opportunity to maintain connections with friends and family. Reports even say these sites and other technology can be useful to kids for staying in touch, socializing, entertainment, and even doing homework and that they can enhance kids’ creativity and help them develop technical skills (Hellmich). Although technology can be useful in some ways like for homework, it is more common that people will become distracted and end up on some other app while trying to do homework, which can lead to too much time spent online can squeeze out other important activities (Hellmich).

In conclusion, people with social media who believe that it is good for them should look around and see all of the various other ways it negatively affects others. Maybe if people who think social media is good and are not addicted to it start to encourage others to limit their time on the apps, our world today could become somewhat better with the relief of a little less negative effects caused by social media. With social media being as big of a deal as it is in our society, it is obvious that it is in all probability not going to come to an end. Although this will not happen, our society can prevent things like bullying and drama caused by social media by limiting our time on apps such as Instagram, Snapchat, and Twitter. 

Works cited

Hellmich, Nanci. “Social Media Websites Can Help and Harm Kids.” USA Today 

28 March 2011, pg. 1.

Winkler, Travis. “Social Networking: Helpful or Harmful.” The Daily 

Pennsylvania, 17 March 2009, pg. 2.

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Social Media Argumentative Essay Topics: 50+ Ideas (2023)

by  Antony W

April 21, 2023

The advent of social media was for one greater cause: to bring people together and enhance interaction regardless of their demography.

Today, the internet has made it easier to connect based on social, economic, and political grounds, with people world apart connecting with the click of a button.

When it comes to social media topics that you can use in an argumentative essay, your options are no doubt unlimited.

In this post, we provide you with 30+ social media argumentative essay topics that you can copy, paste, and start exploring right away.

What is a Social Media Essay?

An argumentative essay on social media allows you to examine the impact of social networking platforms from both sides.

Like any other assignment in the category, you have to take a position on the top and then use logic, reason, and irrefutable evidence to support your claim.

The structure of the argument remains the same, so we won’t dwell much on that.

As you write the essay, you also have to consider and account for the other side of the argument and then use the strongest post or best evidence possible to respond to the counterclaims.

Social Media Argumentative Essay Topics

The following is a list of 30+ topics that you can explore if your instructor has asked you to write a social media argumentative essay:

• Social media is responsible for the destruction of real-life communication
• Should the government ban Facebook, Twitter, and WhatsApp permanently?
• Is our addiction to online social networking out of control?
• Constant social media connection causes stress and loneliness in people
• Can children under the age of 18 own social media accounts?
• Are social media websites effective platforms for communication?
• Social media is the primary source of inferiority complex among teens
• Should Twitter introduce an algorithm that automatically filters negative and aggressive content?
• Does Facebook have the legal right to leave personal information of its users?
• Has social networking reduced the rate of unemployment?
• Should social network users have the right to obscure their identity online?
• Is our culture of online shaming and cyberbullying on Facebook and WhatsApp completely out of control?
• Social media makes teenagers more attracted to their physical appearance
• Does the use of social media make humans feel more alone?
• Should parents have the right to monitor and control what their teen children post on social media?
• The endorsements of celebrities on social media are unethical.
• It’s possible to have a life without social networks at this time
• Should emotional outburst be something we allow on social media?
• Celebrities are a negative influence to the young people on social media
• Is social media addiction at this time easy to control?
• Did Facebook really have to create the “Love” button?
• Are social media owners responsible for the excessive use of abusive language in the comment sections of their platforms?
• Should people with no special skills get famous and become social media celebrities or influencers?
• Are celebrity endorsements on social media misleading to clients?
• Can the use of social media for business help to boost enterprise appeal to the targeted clientele?
• Should human resource hire employees based on what the post on social media?
• Social media cannot help your business to succeed
• Should the government have the right to monitor and control what we post on social media?
• Facebook and WhatsApp groups play a huge role in promoting cyberbullying
• Should individuals first learn how to use caution while posting something online?
• Do social media facilitate or hinder actual communication?
• Are social media platforms undermining the democratic ideal?
• Which between Twitter and Facebook provides a better platform for a company advertisement?
• Are social media destroying the integrity of human relationships?
• Should we utilize social media more frequently to affect lives as opposed to impressing others?
• Does social media addiction enhance dopamine production in the brain?
• Has social media contributed to unrealistic life expectations that frequently result in depression?
• Has the use of social media resulted in greater time loss than any other activity?
• What are the harmful effects of adolescents’ continuous use of social media?
• What harmful behaviors have you developed because of your social media usage?
• Should social platform creators be accountable for harm caused by their platforms?
• Which is more effective, face-to-face or virtual communication?
• Do Family-based reality programs on social media do more damage than good?
• What effects do social media have on the lives of adolescents?
• Does it matter how many likes one receives on social media?
• Should social media users pay to increase their likes and views?
• Do social media control people’s emotions by the content they select to display?
• Due to social networking, personal connections are becoming weaker.
• Have social media decreased the company’s rate of job productivity?
• Which was superior, the world before social media or the world after?
• Should children have the permission to participate in social media?
• Have social media impacted the educational process?
• Is social media a cause of youth discontentment?
• What effect have social media had on the purchasing behavior of consumers?
• Is social media deceptive and mostly irrelevant to an individual’s development?
• Are social paths using social media to attract unwelcome attention?
• Is social media spreading deceptive images of how the world should be?
• Is social media responsible for a rise in adolescent suicide rates?

Social media essays may appear easy to write, but there is just so much overwhelming information on the subject that you may feel stuck on topic selection.

If you need help to get the essay written, especially if you can’t bring yourself to construct solid arguments, you can hire an argumentative essay writer from Help for Assessment for assistance.

Our goal with this service is simple. We want to help you understand the topic you’ve chosen better and help you get the essay written fast. Then, you can use the paper you get from us as reference to write the final draft in your own style and tone. Click here to order .   

How to Write Your Social Media Argumentative Essay

Before you begin writing your essay about social media, you must arrange your themes and ideas in a manner that makes writing much easier. So, here’s how you should approach this assignment:

1. Review the Assignment’s Instructions

The type of essay needed by your instructor will influence the structure you use, so be sure you understand what you must write.

It is also beneficial to read examples of other students’ work, which some tutors may provide. The samples will help you to write a high quality social media essay on a short time.

2. Choose a Topic that Interests You

This may be the most difficult step if your professor does not give a list of potential subjects to investigate. To aid you in narrowing down potential themes for your essay about social media, we have given you some example topics that you can explore.

If you don’t find any of the topics we’ve shared with you to be a good fit for your assignment, simply do additional internet search for more ideas. Alternatively, you can get ask your friends to share some additional ideas with you, especially if they spend most of their time on social media.

3. Research Your Topic

Personal perspectives and experiences may be significant, but you should support them by high-quality scientific evidence. Social media is an important academic field, so there should be enough research materials to help you write an argumentative essay on the subject that you choose.

If you are required to write an essay about social media and its impact, for instance, you should learn about the good and negative effects of social media.

4. Focus on the Main Points

These may contain your ideas, research results, and other pertinent data. Note any fresh ideas that occur to you about your selected topic.

Create an effective thesis statement. What will be the most crucial concept in your essay, based on all you have read? Do you wish to compose an essay about the downsides of social media? Or have you discovered that social networking is significantly more beneficial than most people believe?

Writing a thesis statement that limits the scope of your essay lays the groundwork for its organization.

5. Countercheck Your Points

Recheck your points to determine if any of them do not support your argument. These deletions will assist you in ensuring that your essay is well organized and focused. If you wish to discuss bullying on social media, for instance, you should not include a separate section on the educational uses of social media. Irrelevant remarks may confuse the reader and lose you a few additional points.

6. Write an Essay that Makes Sense

Create section headings that match to your primary points. Writing the titles of each part will assist you in arranging your arguments in a logical fashion. This will guarantee that your essay has a natural flow and is interesting to read.

If certain elements don’t appear to belong together in one area, rearrange them or replace them with relevant assertions.

A conclusion for an essay about social media should summarize your arguments and demonstrate how they support your thesis. Do not include any new material at this point, as doing so may confuse your readers and make your essay appear incomplete.

Tips to Write a Good Social Media Argumentative Essay

The following are some tips that you can use to write a good argumentative essay on social media:

Choose a Topic of Interest

Don’t a topic from your gut. And just because a topic looks good from the face value doesn’t make it a suitable option for your argumentative essay assignment.

Consider choosing a topic that interests you. It can be something you’ve spent a lot of time research lately or an issue you’ve always wanted to explore further.

If you do that, you will have an easy time researching your topic and defending your position on the social media issue you wish to address.

Include Examples in Your Essay

Your readers are interested in knowing why you’ve taken a stand on a given social media issue, even if they don’t currently hold that position.

An interesting way to capture their attention and solidify your position is to include relevant examples in your essay.

These examples should not only be relevant but also be things they can easily identify with or relate to.

For example, if your topic is on “Social Media causing unproductivity at workplace”, you can give relevant examples that show how it creates distraction and lack of attention tom details in workplace.

Use an Outline to Write the Essay

There’s a lot you can write about social media, but you can be sure that most of it is going to be either irrelevant or quite too obvious.

If you want your essay to grab the attention of your professor, use an essay outline for prewriting.

We can’t even start to explain how valuable an outline is. It’s such a powerful framework that lets you organize your thoughts in a logical order.

It also allows you to think those points through and determine whether they’ll be relevant for your social media essay.

Get Social Media Argumentative Essay Writing Help

Don’t let your social media argumentative essay be a burden to you. We at Help for Assessment, through our argumentative essay writing service, can help to point you in the right direction so you can get your work done right.

It doesn’t matter if you feel stuck or you need a step in the right direction, our amazingly talented team is here to help.

About the author 

Antony W is a professional writer and coach at Help for Assessment. He spends countless hours every day researching and writing great content filled with expert advice on how to write engaging essays, research papers, and assignments.

The Grim Reality of Banning TikTok

T he U.S. government, once again, wants to ban TikTok. The app has become an incontrovertible force on American phones since it launched in 2016, defining the sounds and sights of pandemic-era culture. TikTok’s burst on the scene also represented a first for American consumers, and officials—a popular social media app that wasn’t started on Silicon Valley soil, but in China.

On March 13, the U.S. House of Representatives passed a bill to force TikTok’s Chinese parent company, ByteDance, to sell TikTok or else the app will be banned on American phones. The government will fine the two major mobile app stores and any cloud hosting companies to ensure that Americans cannot access the app.

While fashioned as a forced divestiture on national security grounds, let’s be real: This is a ban. The intent has always been to ban TikTok, to punish it and its users without solving any of the underlying data privacy issues lawmakers claim to care about. Texas Rep. Dan Crenshaw said it outright : “No one is trying to disguise anything… We want to ban TikTok.”

But, as such, a ban of TikTok would eliminate an important place for Americans to speak and be heard. It would be a travesty for the free speech rights of hundreds of millions of Americans who depend on the app to communicate, express themselves, and even make a living. And perhaps more importantly, it would further balkanize the global internet and disconnect us from the world.

Read more: What to Know About the Bill That Could Get TikTok Banned in the U.S.

This isn’t the first time the government has tried to ban TikTok: In 2021, former President Donald Trump issued an executive order that was halted in federal court when a Trump-appointed judge found it was “arbitrary and capricious” because it failed to consider other means of dealing with the problem. Another judge found that the national security threat posted by TikTok was “phrased in the hypothetical.” When the state of Montana tried to ban the app in 2023, a federal judge found it “oversteps state power and infringes on the constitutional rights of users,” with a “pervasive undertone of anti-Chinese sentiment.”

Trump also opened a national security review with the power to force a divestment, something Biden has continued to this day with no resolution; and last year, lawmakers looked poised to pass a bill banning TikTok, but lost steam after a high-profile grilling of its top executive. (Trump has done an about-face on the issue and recently warned that banning TikTok will only help its U.S. rivals like Meta.)

TikTok stands accused of being a conduit for the Chinese Communist Party, guzzling up sensitive user data and sending it to China. There’s not much evidence to suggest that’s true, except that their parent company ByteDance is a Chinese company, and China’s government has its so-called private sector in a chokehold. In order to stay compliant, you have to play nice.

In all of this, it’s important to remember that America is not China. America doesn't have a Great Firewall with our very own internet free from outside influences. America allows all sorts of websites that the government likes, dislikes, and fears onto our computers. So there’s an irony in allowing Chinese internet giants onto America’s internet when, of course, American companies like Google and Meta’s services aren’t allowed on Chinese computers.

And because of America’s robust speech protections under the First Amendment, the U.S. finds itself playing a different ballgame than the Chinese government in this moment. These rights protect Americans against the U.S. government, not from corporations like TikTok, Meta, YouTube, or Twitter, despite the fact that they do have outsized influence over modern communication. No, the First Amendment says that the government cannot stop you from speaking without a damned good reason. In other words, you’re protected against Congress—not TikTok.

The clearest problem with a TikTok ban is it would immediately wipe out a platform where 170 million Americans broadcast their views and receive information—sometimes about political happenings. In an era of mass polarization, shutting off the app would mean shutting down the ways in which millions of people—even those with unpopular views—speak out on issues they care about. The other problem is that Americans have the constitutional right to access all sorts of information—even if it’s deemed to be foreign propaganda. There’s been little evidence to suggest that ByteDance is influencing the flow of content at the behest of the Chinese government, though there’s some reports that are indeed worrying, including reports that TikTok censored videos related to the Tiananmen Square massacre, Tibetan independence, and the banned group Falun Gong.

Still, the Supreme Court ruled in 1964 that Americans have the right to receive what the government deems to be foreign propaganda. In Lamont v. Postmaster General , for instance, the Court ruled that the government couldn’t halt the flow of Soviet propaganda through the mail. The Court essentially said that the act of the government stepping in and banning propaganda would be akin to censorship, and the American people need to be free to evaluate these transgressive ideas for themselves.

Further, the government has repeatedly failed to pass any federal data privacy protections that would address the supposed underlying problem of TikTok gobbling up troves of U.S. user data and handing it to a Chinese parent company. Biden only made moves in February 2024 to prevent data brokers from selling U.S. user data to foreign adversaries like China, arguably a problem much bigger than one app. But the reality is that the government has long been more interested in banning a media company than dealing with a real public policy issue.

There is legitimate concern in Washington and elsewhere that it’s not the government that controls so much of America’s speech, but private companies like those bred in Silicon Valley. But the disappearance of TikTok would further empower media monopolists like Google and Meta, who already control about half of all U.S. digital ad dollars, and give them a tighter choke hold over our communication. There’s already a paucity of platforms where people speak; removing TikTok would eliminate one of the most important alternatives we have.

Since it launched in 2016, TikTok has been the most influential social media app in the world, not because it affects public policy or necessarily creates monoculture—neither are particularly true, in fact—but because it has given people a totally different way to spend time online. In doing so, it disrupted the monopolies of American tech companies like Meta, which owns Facebook and Instagram, and forced every rival to in some way mimic its signature style. There’s Facebook and Instagram Reels, YouTube Shorts, Snapchat Spotlight, and every other app seems to be an infinitely-scrolling video these days.

Still, Americans choose to use TikTok and their conversations will not easily port over to another platform in the event of it being banned. Instead, cutting through the connective tissue of the app will sever important ways that Americans—especially young Americans—are speaking at a time when those conversations are as rich as ever.

The reality is that if Congress wanted to solve our data privacy problems, they would solve our data privacy problems. But instead, they want to ban TikTok, so they’ve found a way to try and do so. The bill will proceed to the Senate floor, then to the president’s desk, and then it will land in the U.S. court system. At that point, our First Amendment will once again be put to the test—a free speech case that’s very much not in the abstract, but one whose results will affect 170 million Americans who just want to use an app and have their voices be heard.

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