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300+ Social Media Research Topics

Social media has become an integral part of our lives, and it has transformed the way we communicate, share information, and interact with each other. As social media platforms continue to evolve and gain popularity, they have also become a rich source of data for researchers. Social media research is a rapidly growing field that encompasses a wide range of topics , from understanding the psychological and social effects of social media to analyzing patterns of user behavior and identifying trends in online conversations. In this era of data-driven decision-making, social media research is more important than ever, as it provides insights into how we use and are influenced by social media. In this post, we will explore some of the most fascinating and relevant social media research topics that are shaping our understanding of this powerful medium.

Social Media Research Topics

Social Media Research Topics are as follows:

The effects of social media on mental health
The role of social media in political polarization
The impact of social media on relationships
The use of social media by businesses for marketing
The effects of social media on body image and self-esteem
The influence of social media on consumer behavior
The use of social media for education
The effects of social media on language use and grammar
The impact of social media on news consumption
The role of social media in activism and social change
The use of social media for job seeking and career development
The effects of social media on sleep patterns
The influence of social media on adolescent behavior
The impact of social media on the spread of misinformation
The use of social media for personal branding
The effects of social media on political participation
The influence of social media on fashion trends
The impact of social media on sports fandom
The use of social media for mental health support
The effects of social media on creativity
The role of social media in cultural exchange
The impact of social media on language learning
The use of social media for crisis communication
The effects of social media on privacy and security
The influence of social media on diet and exercise behavior
The impact of social media on travel behavior
The use of social media for citizen journalism
The effects of social media on political accountability
The role of social media in peer pressure
The impact of social media on romantic relationships
The use of social media for community building
The effects of social media on gender identity
The influence of social media on music consumption
The impact of social media on academic performance
The use of social media for social support
The effects of social media on social skills
The role of social media in disaster response
The impact of social media on nostalgia and memory
The use of social media for charity and philanthropy
The effects of social media on political polarization in developing countries
The influence of social media on literary consumption
The impact of social media on family relationships
The use of social media for citizen science
The effects of social media on cultural identity
The role of social media in promoting healthy behaviors
The impact of social media on language diversity
The use of social media for environmental activism
The effects of social media on attention span
The influence of social media on art consumption
The impact of social media on cultural values and norms.
The impact of social media on mental health
The impact of social media on mental health.
The impact of social media on body image and self-esteem.
The use of social media for political activism and social justice movements.
The role of social media in promoting cultural diversity and inclusivity.
The impact of social media on romantic relationships and dating.
The use of social media for customer service and support.
The impact of social media on mental health and well-being among young adults.
The impact of social media on political polarization and partisanship.
The use of social media for health communication and behavior change.
The role of social media in shaping public opinion and attitudes towards vaccination.
The impact of social media on political participation and civic engagement.
The impact of social media on political polarization and echo chambers.
The use of social media for political campaigning and the manipulation of public opinion.
The role of social media in shaping public attitudes towards vaccination and public health.
The impact of social media on news consumption and trust in journalism.
The use of social media for promoting sustainable fashion practices and ethical consumption.
The role of social media in influencing beauty standards and body image.
The impact of social media on the music industry and the role of social media influencers.
The use of social media for promoting mental health and well-being among healthcare professionals.
The role of social media in shaping public attitudes towards gun violence and gun control policies.
The impact of social media on social activism and advocacy.
The use of social media for promoting cross-cultural communication and intercultural understanding.
The role of social media in shaping public attitudes towards climate change and environmental policies.
The impact of social media on public health during the COVID-19 pandemic.
The use of social media for promoting financial literacy and access to financial services for low-income individuals.
The role of social media in shaping public attitudes towards immigration policies and refugee crises.
The impact of social media on political activism and social movements.
The use of social media for promoting digital literacy and technology education in developing countries.
The role of social media in shaping public attitudes towards gender and sexual orientation.
The impact of social media on consumer behavior in the food and beverage industry.
The use of social media for promoting mental health and well-being among first responders.
The role of social media in shaping public attitudes towards racial justice and police brutality.
The impact of social media on privacy concerns and data security.
The use of social media for promoting interfaith dialogue and religious tolerance.
The role of social media in shaping public attitudes towards income inequality and economic justice.
The impact of social media on the film and television industry and consumer behavior.
The use of social media for promoting mental health and well-being among military personnel.
The role of social media in shaping public attitudes towards privacy and data security.
The impact of social media on the hospitality industry and consumer behavior.
The use of social media for promoting intergenerational communication and understanding.
The role of social media in shaping public attitudes towards animal welfare and animal rights.
The impact of social media on the gaming industry and gamer behavior.
The use of social media for promoting digital literacy and technology skills among seniors.
The role of social media in shaping public attitudes towards renewable energy and sustainability.
The impact of social media on the advertising industry and consumer behavior.
The use of social media for promoting mental health and well-being among children and adolescents.
The role of social media in shaping public attitudes towards online privacy and security.
The impact of social media on the beauty industry and consumer behavior.
The use of social media for promoting cultural preservation and heritage tourism.
The role of social media in shaping public attitudes towards criminal justice reform.
The impact of social media on the automotive industry and consumer behavior.
The use of social media for promoting mental health and well-being among marginalized communities.
The role of social media in shaping public attitudes towards sustainable development goals.
The impact of social media on the fashion industry and consumer behavior.
The use of social media for promoting intercultural communication in the workplace.
The role of social media in shaping public attitudes towards mental health policies.
The impact of social media on the travel industry and sustainable tourism practices.
The use of social media for health information seeking and patient empowerment.
The role of social media in promoting environmental activism and sustainable practices.
The impact of social media on consumer behavior and brand loyalty.
The use of social media for promoting education and lifelong learning.
The role of social media in shaping public opinion and attitudes towards mental health issues.
The impact of social media on the fashion industry and fast fashion practices.
The use of social media for promoting social entrepreneurship and social innovation.
The role of social media in shaping public opinion and attitudes towards gun control.
The impact of social media on the mental health and well-being of adolescents.
The use of social media for promoting intercultural exchange and understanding.
The role of social media in shaping public opinion and attitudes towards climate change.
The impact of social media on political advertising and campaign strategies.
The use of social media for promoting healthy relationships and communication skills.
The role of social media in shaping public opinion and attitudes towards police brutality and racial justice.
The use of social media for promoting financial literacy and personal finance management.
The role of social media in shaping public opinion and attitudes towards LGBTQ+ rights.
The impact of social media on the music industry and fan engagement.
The use of social media for promoting mental health and well-being among marginalized populations.
The role of social media in shaping public opinion and attitudes towards immigration and border policies.
The impact of social media on the professional development and networking of journalists.
The use of social media for promoting community building and social cohesion.
The role of social media in shaping public opinion and attitudes towards healthcare policies.
The impact of social media on the food industry and consumer behavior.
The role of social media in shaping public opinion and attitudes towards gender equality.
The impact of social media on the sports industry and athlete-fan interactions.
The use of social media for promoting financial inclusion and access to banking services.
The role of social media in shaping public opinion and attitudes towards animal welfare.
The use of social media for promoting mental health and well-being among college students.
The role of social media in shaping public opinion and attitudes towards privacy and data security.
The role of social media in shaping public opinion and attitudes towards income inequality and poverty.
The use of social media for promoting digital literacy and technology skills.
The role of social media in shaping public opinion and attitudes towards renewable energy.
The use of social media for promoting mental health and well-being among elderly populations.
The role of social media in shaping public opinion and attitudes towards online privacy and security.
The role of social media in shaping public opinion and attitudes towards criminal justice reform.
The impact of social media on online activism and social movements.
The use of social media for business-to-business communication and networking.
The role of social media in promoting civic education and engagement.
The impact of social media on the fashion industry and sustainable fashion practices.
The use of social media for promoting cultural diversity and inclusion.
The role of social media in shaping public opinion and attitudes towards police reform.
The impact of social media on the mental health and well-being of frontline healthcare workers.
The use of social media for promoting financial literacy and investment education.
The role of social media in promoting environmental sustainability and conservation.
The impact of social media on body image and self-esteem among adolescent girls.
The use of social media for promoting intercultural dialogue and understanding.
The role of social media in shaping public opinion and attitudes towards immigration policies and refugees.
The impact of social media on the professional development and networking of healthcare professionals.
The use of social media for promoting community resilience and disaster preparedness.
The role of social media in shaping public opinion and attitudes towards the Black Lives Matter movement.
The impact of social media on the music industry and artist-fan interactions.
The use of social media for promoting healthy eating habits and nutrition education.
The role of social media in promoting mental health and well-being among college students.
The impact of social media on the entertainment industry and consumer behavior.
The use of social media for promoting workplace diversity and inclusion.
The role of social media in shaping public opinion and attitudes towards climate change policies.
The impact of social media on the travel industry and consumer behavior.
The use of social media for promoting mental health and well-being among military veterans.
The role of social media in promoting intergenerational dialogue and understanding.
The impact of social media on the professional development and networking of educators.
The use of social media for promoting animal welfare and advocacy.
The role of social media in shaping public opinion and attitudes towards reproductive rights.
The impact of social media on the sports industry and fan behavior.
The use of social media for promoting financial inclusion and literacy among underprivileged populations.
The role of social media in promoting mental health and well-being among LGBTQ+ populations.
The impact of social media on the food and beverage industry and consumer behavior.
The use of social media for promoting interfaith dialogue and understanding.
The role of social media in shaping public opinion and attitudes towards gun ownership.
The use of social media for promoting mental health and well-being among caregivers.
The role of social media in promoting sustainable tourism practices.
The impact of social media on the gaming industry and gamer culture.
The use of social media for promoting cultural heritage tourism and preservation.
The role of social media in shaping public opinion and attitudes towards public transportation policies.
The use of social media for promoting mental health and well-being among homeless populations.
The role of social media in promoting mental health and well-being among immigrants and refugees.
The use of social media for promoting financial literacy and entrepreneurship among youth.
The use of social media for political mobilization and participation in authoritarian regimes.
The role of social media in shaping public opinion and attitudes towards immigration policies.
The impact of social media on the professional development of teachers and educators.
The use of social media for emergency communication during public health crises.
The role of social media in promoting LGBTQ+ rights and advocacy.
The impact of social media on body positivity and self-acceptance among women.
The use of social media for public diplomacy and international relations.
The impact of social media on the mental health and well-being of marginalized communities.
The use of social media for crisis management and disaster response in the corporate sector.
The role of social media in promoting environmental activism and conservation.
The impact of social media on the professional development and networking of entrepreneurs.
The use of social media for medical education and healthcare communication.
The role of social media in promoting cultural exchange and understanding.
The impact of social media on social capital and civic engagement among young adults.
The use of social media for disaster preparedness and community resilience.
The role of social media in promoting religious pluralism and tolerance.
The use of social media for promoting healthy lifestyles and wellness.
The use of social media for fundraising and philanthropy in the non-profit sector.
The role of social media in promoting interfaith dialogue and understanding.
The impact of social media on the travel and tourism industry and consumer behavior.
The use of social media for customer engagement and brand loyalty in the retail sector.
The impact of social media on the political attitudes and behaviors of young adults.
The use of social media for promoting gender equality and women’s empowerment.
The use of social media for promoting animal welfare and adoption.
The role of social media in promoting mental health and well-being among the elderly.
The impact of social media on the art industry and artist-fan interactions.
The use of social media for promoting healthy food choices and nutrition.
The role of social media in shaping public opinion and attitudes towards income inequality.
The use of social media for promoting political satire and humor.
The role of social media in promoting disability rights and advocacy.
The use of social media for promoting voter registration and participation.
The role of social media in promoting entrepreneurship and small business development.
The use of social media for promoting mental health and well-being among incarcerated populations.
The role of social media in shaping public opinion and attitudes towards gun violence prevention.
The use of social media for promoting cultural heritage and preservation.
The impact of social media on mental health and well-being.
The relationship between social media use and academic performance.
The use of social media for emergency communication during natural disasters.
The impact of social media on traditional news media and journalism.
The role of social media in shaping public opinion and discourse.
The use of social media for online learning and education.
The impact of social media on the fashion and beauty industry.
The use of social media for brand awareness and marketing.
The impact of social media on privacy and security.
The use of social media for job searching and recruitment.
The impact of social media on political polarization and extremism.
The use of social media for online harassment and cyberbullying.
The role of social media in promoting environmental awareness and sustainability.
The impact of social media on youth culture and identity formation.
The use of social media for travel and tourism marketing.
The impact of social media on consumer behavior and decision-making.
The role of social media in shaping beauty standards and body positivity.
The use of social media for crisis communication and disaster response.
The impact of social media on the music industry.
The use of social media for fundraising and philanthropy.
The role of social media in promoting healthy lifestyles and wellness.
The impact of social media on sports fandom and fan behavior.
The use of social media for political lobbying and advocacy.
The impact of social media on the entertainment industry.
The use of social media for healthcare communication and patient engagement.
The role of social media in promoting gender equality and feminism.
The impact of social media on the restaurant and food industry.
The use of social media for volunteerism and community service.
The role of social media in promoting religious tolerance and interfaith dialogue.
The impact of social media on the art industry.
The use of social media for political satire and humor.
The role of social media in promoting disability awareness and advocacy.
The impact of social media on the real estate industry.
The use of social media for legal advocacy and justice reform.
The role of social media in promoting intercultural communication and understanding.
The impact of social media on the automotive industry.
The use of social media for pet adoption and animal welfare advocacy.
The role of social media in promoting mental health and wellness for marginalized communities.
The impact of social media on the retail industry.
The use of social media for promoting civic engagement and voter participation.
The impact of social media on the film and television industry.
The use of social media for fashion and style inspiration.
The role of social media in promoting activism for human rights and social issues.
The effectiveness of social media for political campaigns.
The role of social media in promoting fake news and misinformation.
The impact of social media on self-esteem and body image.
The impact of social media on romantic relationships.
The use of social media for online activism and social justice movements.
The impact of social media on traditional news media.
The impact of social media on interpersonal communication skills.
The impact of social media on the fashion industry.
The use of social media for social support and mental health awareness.
The use of social media for political lobbying and activism.
The impact of social media on travel and tourism behavior.
The use of social media for customer feedback and market research.
The impact of social media on the restaurant industry.
The role of social media in political activism
The effect of social media on interpersonal communication
The relationship between social media use and body image concerns
The impact of social media on self-esteem
The role of social media in shaping cultural norms and values
The use of social media by celebrities and its impact on their image
The role of social media in building and maintaining personal relationships
The use of social media for job searching and recruitment
The impact of social media on children and adolescents
The use of social media by political candidates during election campaigns
The role of social media in education
The impact of social media on political polarization
The use of social media for news consumption
The effect of social media on sleep habits
The use of social media by non-profit organizations for fundraising
The role of social media in shaping public opinion
The influence of social media on language and communication patterns
The use of social media in crisis communication and emergency management
The role of social media in promoting environmental awareness
The influence of social media on music preferences
The impact of social media on body positivity movements
The role of social media in shaping beauty standards
The influence of social media on sports fandom
The use of social media for health promotion and education
The impact of social media on political participation
The role of social media in shaping parenting practices
The influence of social media on food preferences and eating habits
The use of social media for peer support and mental health advocacy
The role of social media in shaping religious beliefs and practices
The influence of social media on humor and comedy
The use of social media for online activism and social justice advocacy
The impact of social media on public health awareness campaigns
The role of social media in promoting cultural diversity and inclusion
The influence of social media on travel behavior and decision-making
The use of social media for international diplomacy and relations
The impact of social media on job satisfaction and employee engagement
The role of social media in shaping romantic preferences and dating behavior
The influence of social media on language learning and language use
The use of social media for political satire and humor
The impact of social media on social capital and community building
The role of social media in shaping gender identity and expression
The influence of social media on fashion and beauty advertising.

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74 Best Social Media Research Paper Topics

Whether in college or high school, you will come across research writing as a student. In most cases, the topic of research is assigned by your teacher/professor. Other times, students have to come up with their topic. Research writing in school is inescapable. It’s a task you are bound to undertake to fulfill your academic requirements. If you are in college, there are several topics for research depending on your discipline. For high school students, the topic is usually given. In this article, we focus on social media and topics about social media.

A social media paper is a research paper about social media that studies social media generally or an aspect of it. To write research papers on social media, you’ll need to conduct thorough research for materials and scholarly materials that’ll assist you. For social media, most of the scholarly works will be media-focused.

Sometimes, Professors or teachers ask students to write an essay or research a topic without narrowing it down. In that case, students will have to develop specific research topics. If you’re writing a paper on social media, we’ve provided you with helpful topics to consider for research.

How to Start a Social Media Research Paper

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Before giving a research writing, Professors and teachers believe students already know how to write one. Not every student knows how to write a research paper in most cases.

Research writing follows a systematic pattern, which applies to research on social media. Below is the pattern of a research paper to use;

Paper title
Introduction
Statement of problem
Research methodology
Research objective
Critical analysis
Results and discussion

Every research follows this basic pattern, and it also applies to your research paper on social media.

Social media has become a powerful tool for engagement of various kinds. Before now, social media was merely apps used for interpersonal affairs. Today, with the modification of digital technology, social media encompasses a lot more. Below are some social media topics to write about.

The impact of social media in promoting interpersonal relationships
A study on how social media is a vital tool for social change
Social media censorship: A new form of restriction on freedom of speech
The constantly growing oversharing nature of social media
Social media is a vital tool for political campaign
The proliferation of social media platforms into a buying space
The juxtaposition of personal engagement and business on social media platforms

There is a wide range of topics to coin from social media for college students because social media is a platform with diverse issues that can form into topics. Here are some research topics about social media to consider.

Breach of Privacy: A study on the ability of the government to monitor personal affairs on social media
A study of the toxicity brewing within social media
The increased cyberbullying perpetrated on social media platforms
The evolution of Twitter into a space for diverse conversations
A study of the emergence and growth of social media over the years
Effects of social media: How social media is breeding laziness amongst children
Social media as a distraction tool for students

If you are searching for interesting topics, there are many interesting research topics on social media. Examples of research paper topics that sound fun to choose from include;

A study on how the emergence of social media and social media advertising has infiltrated its primary purpose
An evaluation of how social media has created employment opportunities for people
Social media influence and its negative impact on society
Advertising on social media: Will influencer businesses take over advertising agencies?
A study on ways to improve advertisement for social media engagement
A look into how social media creates a distorted view of real life
Social media and real-life: Does social media obscure reality?

Research questions are helpful when carrying out research in a particular field. To know more about your thesis on social media, you will need to create research questions on social media to help inform your writing. Some social media research questions to ask are;

Are social media platforms designed to be addictive?
What is a social media Algorithm, and how to navigate it?
To what extent are personal data stored on social app databases protected?
Can social media owners avoid government monitoring?
Should parents allow their children to navigate social media before they are 15?
Have social media jobs come to stay, or are they temporary?
Is social media influencer culture overtaking celebrity culture?
To what extent can social media help to curb racism and homophobia?
Does social media exacerbate or curb discriminatory practices?
Is social media an effective tool for learning?

Everyone has access to social media apps until they’ve reached a certain age. There are several social media essay topics for high school students to write about. Some social media titles for essays include;

How social media affects the academic performance of students
Why the use of social media is prohibited during school hours
Why students are obsessed with Tiktok
Running a profitable social media business while in high school and the challenges
The dangers of overusing editing apps
A critical essay on how editing apps and filters promote an unrealistic idea of beauty
The death of TV: how social media has stolen student’s interest

The challenge students have with their topic ideas for research papers is that they’re broad. A good social media thesis topic should be narrowed down. Narrowing a topic down helps you during research to focus on an issue.

Some narrow social media topics for the research paper include;

A study of how social media is overtaking Television in entertainment
A study of how social media has overtaken traditional journalism
An evaluation of the rise of influencer culture on Instagram
YouTube and how it has created sustainable income for black content creators
A comparative study of social media managers and content creators
A study of the decline of Instagram since the emergence of Tiktok
How Twitter breeds transphobic conversations

There are several areas of social media to focus your research on. If you are looking for some social media marketing topics, below are some social media research paper topics to consider;

Influencer culture and a modified model of mouth-to-mouth marketing
The growth of video marketing on Instagram
Social media managers as an essential part of online marketing
A study on how social media stories are optimized for marketing
An analysis of social media marketing and its impact on customer behavior
An evaluation of target marketing on social media

There are so many topics to choose from in this aspect. Some social issues research paper topics to explore are;

The growth of cyberattacks and cyberstalking in social media
Social media and how it promotes an unrealistic idea of life
Social media and the many impacts it has on users and businesses
Social media detox: Importance of taking scheduled social media breaks
How social media enable conversation on social challenges

Writing a research paper on social issues touches on various areas. Some are challenging, while others are easier to navigate.

Below are some of the easy social issues topics to choose from.

The growing issue of women’s and trans people’s rights
Religious bigotry and how it affects social progress
Sustainable living and why it’s important to the society
The social impact of climate change and global warming

Social science is a broad discipline. If you are looking for social science essay topics, below are some social science topics for research papers to look into;

Consumerism and how it’s perpetrated on social media
How religious beliefs impact social relationships
Inflation and how it affects the economy of a nation
A study of the limited availability of work opportunities for minority groups
A look into the concept of “low wage” jobs

Research writing is not always technical or challenging. Sometimes, it can be fun to write. It all depends on your choice of topic. Below are some topics on social media that are fun to work on;

The importance of social media branding for small businesses
A look into the monetization of Instagram
User engagement and how it can be converted into business leads
The study of emojis and their role in social media engagement
From Instagram to Tiktok: the poaching nature of social media apps

Research writing on social media networking studies social networking and its design and promotion on social media platforms. Some research papers on social media networking are;

The impact of social media networking on business owners
Social media networking and how it impacts influencer culture
Social media and how it’s used to build and develop social relationships
How social media made social networking services easier

Social media research writing is one of the most interesting research to conduct. It cuts across several interesting areas. The writer can handle almost every aspect of the dissertation or thesis statement about social media . But, students who find it challenging should seek professional help. You can reach out to our expert team of writers to help you handle every element of your writing. We have the best on our team who are always ready to give you their best.

The Top 10 Most Interesting Social Media Research Topics

Finding social media research topics you’re interested in is tricky. Social media is a fairly new field, and the constant arrival of new technology means that it’s always evolving. So, students have a lot to think about in their search for topics.

In this article, we’re going to walk you through social media research paper topics that are timely and relevant. We’ll also show you examples of social media research topics you can get inspiration from. Lastly, we’re going to lay out some social media research questions you can ponder while formulating your topic.

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What makes a strong social media research topic.

A strong social media research topic requires clarity of focus. This means that your topic must be timely, relevant, and coherent. This allows your research topic to be compelling and easily understandable to others.

Tips for Choosing a Social Media Research Topic

Know the trends. Learning what social media topics are trending allows you to know the relevant issues and emergent themes in the field of social media. This also lets you know what topics are well-researched and which ones are still emerging.
Explore knowledge gaps. Knowing what previous researchers have written prevents you from repeating knowledge that has already been explored and shared. Nobody wants to reinvent the wheel when doing research. Exploring knowledge gaps lets you increase the impact of your work and identify opportunities for further research.
Choose something that you’re interested in. Diving deep into a topic that you’re interested in motivates you to learn more about it. The research process becomes more engaging when you know you care about your topic.
Be specific. Knowing what you want to research and what you don’t want to research are keys to the research process. This entails narrowing down your topic to a specific area, subject, theme, or relationship. You want to know the scope and the limitations of your study.
Check your timeframe. Limiting your topic to a specific timeframe helps in narrowing down what you need to study. For example, you can decide to study a phenomenon that has emerged in just the last three years. By doing this, you’re making sure that your research is both specific and relevant.

What’s the Difference Between a Research Topic and a Research Question?

The difference between a research topic and a research question is in the scope. Research topics tend to be broader than research questions. Research topics focus on a specific area of study within a larger field, while a research question further narrows down what you are researching. A good research question allows you to write on your topic with greater precision.

How to Create Strong Social Media Research Questions

The key to creating strong social media research questions is learning enough about your topic to know where the gaps are. This means that you have to conduct a thorough social media literature review, reading previous studies until you have a handle on what’s been said and what questions are still unanswered. Your question will emerge from this preliminary research.

2. The Influence of Social Media on Mental Health

Mental health has been an important topic in social media research these past few years. Social media use and its connection to mental health has even been the subject of systematic reviews. This means that there’s a huge body of previous studies that you can look to when developing your research question.

Exploring both the positive effects and negative impacts of social media sites on mental health helps people and firms establish guidelines that help user communities. This research topic might also cover strategies for helping social media users improve their mental health.

3. The Role of Social Media in Political Campaigning

Social media is a new tool for political campaigning. Exploring what social media strategies have been conducted by politicians running for office helps in determining how social media aids in political campaigning. Studying new strategies like user-generated content for political campaigning allows you to know how voters interact with political candidates.

4. The Role of Social Media in Disinformation

The rise of fake news has coincided with the rise of social networking websites. This topic involves dissecting how social media technologies allow certain types of online content to thrive and make it easier for bad actors to spread disinformation.

5. How Social Media Can Benefit Communities

More and more social issues have been popularized through online content. Diving deep into how social media can facilitate organizational networking lets you compare the traditional and new organizing strategies being created in digital spaces. It also lets you understand how social media activity influences trends in virtual communities.

6. The Effects of Social Media Exposure on Child Development

Children also use social media sites. Some children use social networking sites under the supervision of their parents, and some do not. Social interaction, online or not, affects how children develop. Studying the psychological effects of social media exposure lets you know how social media may improve or derail the growth of children.

7. How Communication Has Evolved Through Social Media

Body language, tone of voice, and other non-verbal cues are absent in online forms of communication. In their place, emojis and other new ways to express thoughts and emotions have appeared. Learning how social media changes the way we talk to one another allows you to develop a theory of communication that takes into account the role of digital communities.

8. Social Media Platforms as Primary News Sources

A lot of people now are getting their daily dose of news and current events through social media. News networks have also established their social media presence on platforms that they can use to deliver news and current events to their audiences. Researching this topic lets you investigate the changes and innovations in information dissemination.

9. How Social Media Paves Way for Non-Traditional Advertising

Regular social media posts, advertisements, and other forms of online content aren’t the only ways businesses market to their audiences. Social media has paved the way for user-generated content and other non-traditional types of online marketing. With this topic, you can learn social media marketing strategies that have been capitalized on the social connection fostered by social networking websites.

10. Impacts of Social Media Presence on Corporate Image

More businesses increasingly build and curate their digital presence through various social networks. Knowing how a business can improve its corporate image through social media influence clarifies the role of technology in modern economics and online marketing.

Social Media Research Questions

How was Facebook used as a political campaigning tool in the 2020 United States presidential election?
What social platforms are the most effective in influencing consumer behavior?
How does user-generated content boost the credibility of a business?
How do different types of online content disseminated through popular networks affect the attention span of people?
What are the most effective forms of online content and social media strategies for increasing sales conversions for small businesses?

Choosing the Right Social Media Research Topic

Choosing the right social media research topic helps you create meaningful contributions to the discipline of social media studies. Knowing the most popular topics in the field can make you an expert on social media. By reading up on previous studies, you will not only be more informed but you will also be in a position to make a positive impact on future studies.

Studying the relationship between social media and different fields produces valuable knowledge. Even if you’re only interested in exploring one social platform or a single social media event or phenomenon, your research can help people better understand how social media engagement changes the face of social relationships in the world at large.

Social Media Research Topics FAQ

Social media is a computer-based technology that allows digital communities to exchange information through user networks. Various social media networks specialize in text, photo, or video transfer. All of these are ways for people on the Internet to share information and ideas with each other.

Social media research is important because it helps you contribute to the growing body of knowledge about digital social settings. In 2021, according to DataReportal, at least 4.88 billion people around the world use the Internet . The more that people connect with each other through the social media domain, the more their quality of life changes, for better or worse.

According to Statista, the most popular social media platforms right now are Facebook, YouTube, and WhatsApp , each of which has at least two billion users. These social networks allow users to share text, picture, and video content with one another.

People use social media to connect with each other, share information, and entertain themselves. Social media sites can broadly serve all of these purposes or be focused on just one of these functions.

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MRA Guide to the Top 16 Social Media Research Questions

MRA and IMRO published this simple guide to Social Media Research (SMR) in 2010 in order to help researchers identify and find answers to the most important questions to SMR techniques.

Introduction Social networks engulf everyday life. They represent a place to share news, ideas, and information of all kinds. The connections made among people in these networks, and the resulting information shared, can have a profound effect on the thoughts, attitudes, and beliefs of individuals. Moreover, even the flow of information itself can be a powerful predictor of key business and program outcomes.

Recognizing the power of social networks, opinion researchers have increasingly begun to take advantage of social media to answer critical business questions. In doing so, the research profession has invented new tools and methods to supplement an already impressive array of techniques. The Marketing Research Association (MRA) has developed this guide in order to describe the current landscape of social media research as well as to facilitate and advance further development of the technique. Ultimately, it is the goal of the Association and its members to foster universally accepted and practiced standards and best practices for these and other research methods.

What is Social Media?

There are many definitions of social media but, at its core, social media uses Internet-based technologies that facilitate the creation and exchange of user-generated content. Social media refers to Web sites that permit people to interact with the site and with each other using simple interfaces. At the time of publication, Facebook, qq.com, Twitter and YouTube are among the most popular social media sites.

Social media refers to the information that people share on those sites, including status updates, image and video comments, responses to blogs and forums, and any other individual contributions to the online space. This information reflects naturally occurring conversations among people who may or may not personally know each other.

What is Social Media Research?

Though evolving rapidly, social media research (SMR) is the application of marketing and opinion research methods to social media data for the purposes of conducting research (e.g., usage and attitude studies, social media research tracking studies, custom research, etc.). Similar to other types of marketing research usage and attitude studies, tracking studies, research goals and objectives are developed, methodologies are prepared, and social media data are analyzed quantitatively and/or qualitatively depending on the goals of the project.

SMR is distinct from other forms of marketing research in that it uses social media as its data source as opposed to surveys, focus groups and other data collection modes and techniques. SMR can be a complementary or stand-alone analytical tool for researchers, providing them with a unique opportunity to listen and measure the opinions of potentionally vast numbers of people who communicate online, some of whom may not normally or easily be accessible through non-observational forms of research.

About the Authors MRA is grateful to the following for their contributions to this Guide to the Top 16 Social Media Research Questions: Jim Longo, PRC, Itracks, Committee Chair; Janet Savoie, PRC, Online Survey Solution; Annie Pettit, Conversition Strategies; Ray Poynter, The Future Place; Ellie Schwartz; Ed Sugar, PRC, OLC Global; Tamara Barber, Forrester Research; Tamara Kenworthy, PRC, On Point Strategies; Steven Runfeldt, Schwartz Consulting; Benjamin Smithee, Spych Market Analytics; Aaron Hill, PRC, Sawtooth Software; Susan Saurage-Altenloh, PRC; Steffen Hück, HVYE; and Patrick Glaser, MRA.

THE ROLE OF SOCIAL MEDIA RESEARCH

#1. what are the advantages and disadvantages of smr.

From a capacity standpoint, SMR provides the ability to collect and analyze information from the past as well as in real-time, as it is generated. Moreover, the richness of data available on social media networks is conducive to both qualitative designs (e.g., digital ethnographies) as well as quantitative designs, including numerical aggregation of large quantities of data.

In terms of methodological considerations, SMR utilizes an observational form of data collection. Information is collected from Web sites as posted by individuals who may not be specifically aware of the research role. As such, social media communications are thought to be free of, or less subject to, response biases that occurs in interviewer-administered, and even self-administered, forms of opinion surveys and focus groups. However, social media is inherently a public form of communication, with varying degrees of privacy which may affect some social media users’ willingness to reveal information, particularly sensitive or potentially embarrassing personal details.

From an ethical standpoint, SMR has the additional advantage of eliminating the burden that would otherwise be placed on a research participant. Social media users do not participate in “active” data collection (e.g., survey, focus group). They generate data simply by engaging in their natural online communications. However, SMR presents unique ethical considerations of which researchers must be aware (see “Ethical and Legal Issues”).

SMR offers researchers a host of benefits, a few of which include:

Ease of adjusting research criteria throughout the study
Potential cost savings and reduced logistical burden
Ease of application across locations
Access to hard-to-reach research participants
Benchmarking (e.g., reported vs. observed opinions)

Likewise, researchers should be aware of various challenges associated with SMR. For example, researchers who are new to SMR methods will need to familiarize themselves with both the characteristics of social media users as well as specific SM sites in order to properly draw conclusions about research findings. Additional considerations include the need to learn and become proficient with:

SM tools and techniques including sentiment and content analysis
Indicators of SMR validity and reliability at each stage of the process
Relevant types of biases, particularly those arising from unique SMR tools
The types of brands and categories that are more likely to be successful carrying out SMR, e.g., due to volume of data or consumer importance

#2. What data sources are typically used in SMR?

Millions of Web sites (small and large) currently facilitate the practice of social media research. However, online sites, which currently facilitate social media communications come and go, and change very rapidly. Researchers involved in SMR need to stay abreast of changes in social media communication patterns and trends, including the rise of mobile access, and popular SM vehicles. Current examples of SM Web sites that generate data suitable for SMR include:

Social Networking Sites:Social News: e.g., Digg, Reddit, Mashable, Technorati Facebook: Search, Community Pages, Fan Pages, Groups, Chat, Facebook-based Apps

Twitter: Location-based Application, Real-time Search, Advanced Search (search.twitter.com)

LinkedIn: Search, Groups, Q&A

Photo/Video Sharing: e.g., YouTube, Flickr
Online Communities: Industry, Topic-related, Branded or Unbranded
Blogs: e.g., Blogger, Posterous, Wordpress
Forums: Industry or Topic-related
Questions and Answers: e.g., Yahoo Answers, Linkedin Answers, Yedda
Commenting: e.g., Disqus, Backtype
Traditional News: e.g., CNN, BusinessWeek

#3. How does SMR interact with other forms of traditional and non-traditional research, including online, offline, in-person, and qualitative and quantitative?

SMR can effectively stand on its own, but may also be integrated with traditional research methods to create a holistic research solution. In fact, SMR may sometimes springboard or support other forms of traditional research. Examples of SMR integration with other research methods include:

Observing the flow of conversation in real time, thus prompting the most effective methodology for further research
Accessing user supplied media such as photos and video
Measuring trending topics for further “traditional” research
Assisting in the preparation of discussion guides or surveys
Identifying key influencers in an industry or on a topic
Reaching a segment of the population that may not otherwise be reachable
Comparing community-based insights to natural observational social media insights
Establishing trust between researcher and participant, potentially for further recruitment into another form of research
Exploring, and discovering “unknowns” via observations

#4. How reliable are SMR results?

Validity refers to the degree to which results reflect truth or reality while reliability reflects the degree to which results can be replicated if someone else were to conduct a similar study. Because research suppliers have different methods, standards of quality, and processing rules, research consumers must conduct their own validity and reliability analysis of any potential supplier to ensure the quality of work is sufficient. As with all types of marketing research, the validity and reliability of social media research varies greatly:

What is the validity and reliability of the sentiment and/or content analysis processes? If manual coders are used, reliability might be lower. If automated coders are used, validity might be lower.

Given that sentiment differs by Web site (e.g., Twitter is more negative while blogs are more positive), what is the range of social media venues that are measured and what percentage of the Internet population do they represent? Do any of the sites overwhelm the data collection strategy in a proportion that does not reflect the Internet space? Does the vendor know how and why to sample and weight data?
To what extent is the intended target group reflected by the social media venues being used?
Is the intention to measure and generalize to the general Internet population or to a particular segment of the Internet?
How is geographic and demographic information being measured in order to assess the validity of generalizing outside of the sample?
What timeframe is appropriate for the research objectives? Though small samples may be acceptable for long-term research, shorter time frames must use larger sample sizes.

#5. Within businesses and organizations, how will SMR activities be tracked and aggregated, and whose responsibility is it to handle each of those functions?

Social media research may be executed in multiple ways. For example, numerous departments within a single company may be involved in SMR, including internal research departments, and cross-functional teams from marketing, customer relationship management, public relations, public affairs, and other departments. SMR may also be outsourced to vendors who may or may not specialize in research. Regardless, the skill set of the user must be appropriate for the function.

#6. What additional knowledge, skills, and abilities will a corporate researcher need to learn in order to improve their level of competency with SMR?

SMR may involve several different methods and analytical approaches. As such, corporate researchers may find it most advantageous to learn a wide breadth of relevant techniques while continually honing their skills and knowledge in the areas that are most relevant to their organization. Commonly used techniques include both sentiment analysis and content analysis. Additionally, researchers will need to learn about, and become comfortable with, important explanatory variables beyond traditional “respondent” demographics, such as how different types of Web sites (e.g., blogs, forums, media, etc.) generate and facilitate different types of data (e.g., whether data is more positive versus negative, descriptive versus condensed, etc.).

#7. Are the participants aware that their usergenerated content is under observation?

Research contributors have demonstrated the occasional tendency to provide sub-optimal information when they are aware that others are studying or observing them. Oftentimes, this is attributable to concerns over the privacy of sensitive information or feelings of being compelled to give a socially-desirable response to a question. In SMR, though it commonly is understood that conversations are generally public and open to viewing by almost anyone, the individual under observation may or may not be aware of the presence of a researcher.

At the same time, participation in the social media space offers varying degrees of privacy. Users may participate for personal and/or professional reasons and they may or not seek relationships with other users. Researchers should be aware of the potential and likelihood for “social observational bias” and the effect it will have on the type, candor and direction of the user’s comments.

Ethical and Legal Issues

#8. how are sources cited in research reports and on research web portals are the citations different based on the source, e.g., twitter, blogger, forums.

As in traditional forms of research, it is important to protect the privacy of contributors. As such, without prior express consent, data transmitted from vendor to client should not include direct references or citations to individuals that would reveal their identity.

However, sources may be recorded for validation purposes as well as for potential data quality checks. Any data or reporting intended for transfer to an outside entity should be purged of personally identifiable information (PII) prior to changing-hands. This includes IP addresses, usernames, user id numbers, user photos, e-mail addresses, and other types of commonly available online data.

Where detailed information must be shared for the purposes of data quality or validation, the data should include source citations using the current link of the information (e.g., http:// twitter.com/xxxx/xxxx/). Notably, links should be expected to expire or become “broken” overtime. Researchers should plan to record any pertinent administrative or relevant source data (e.g., date/time, source identifier, query details, etc.) to be used in validation at the time of data collection.

#9. What are the controversies and legal issues regarding the rights of the people whose data is being used?

Social media is a relatively new form of communication and individuals from every stakeholder group, including the public, researchers and governments, are participating in an on-going conversation about the nature of its privacy and ethics. For this reason, it’s critical for researchers to understand that they have a responsibility to respect social media user’s privacy and that the definition and expectations for social media user’s privacy can and will change over time. Some brief areas of consideration are described below.

Privacy: Individuals and their social media privacy expectations should be respected. If an individual has posted information on a public Web site under a public “privacy” setting, they may be considered to have a very low or no expectation of privacy for the information they reveal. Even so, researchers who collect and analyze this information should take care to protect it from becoming identifiable to an individual.

Conversations should not be copied verbatim into reports as those direct quotes can be searched and identities discovered. A small number of relevant conversations can be summarized, without losing their flavor, in reports. Moreover, full quotations can be used with permission.

Interacting with individuals: Clients must never use information collected during or for social media research for the purpose of direct marketing or otherwise influencing the opinions and behaviors of the data subject. Marketing may only occur in places like branded and client communities where contributors would naturally expect those types of conversations to take place.

Combining data from multiple sources where privacy policies differ: In general, the policy provisions that tend to favor the rights and needs of the contributors should be given weight. Best practices call for researchers to respect the coded crawling terms of every Web site they visit. Where Web sites are coded to indicate that crawling is not permitted, those Web sites should not be crawled even if it is technically possible. Researchers must not join Web sites under the pretense of being a member so that they then have access to crawl a Web site that prohibits such crawling otherwise – this condition holds for both automated and manual crawling. Where researchers do join groups, they must immediately make it explicit that they are there for the purposes of marketing research. Notably, issues concerning access to data sources are paramount to the conduct of social media research and can be expected to be a major focus of the opinion research industry moving forward, both in terms of how to ethically gain access to the widest net of sources as well as appropriate ways to handle and adjust for cases where this is not possible.

SM Research Processes & Providers

#10. what is the level of expertise and industry qualifications of social media researchers and/or smr companies.

Anyone selecting a social media research vendor must be aware that the technique is relatively new. They must be careful to select a research partner with the appropriate level of expertise and skill in the practice of SMR. Some relevant questions to ask include:

Is the company primarily an IT or social media company that expanded into research, or a research company that expanded into social media? While IT and social media companies may have expertise in social media, crawling and data collection techniques, research companies have expertise in data analysis techniques.
Does the company focus on research exclusively or do they maintain other functions as well? For example, companies that conduct SMR may specialize in buzz monitoring, customer relationship management, public relations, research, or some other social media function.
Does the company specialize in qualitative methods, quantitative methods, or a combination of both?
Is the provider aware of traditional research practices such as sampling and weighting and, if so, how and when do they apply those practices?
For the practice of ethics and standards of quality, does the provider classify themselves as a researcher or as some other profession?

#11. What are the standard data and/or research outputs?

Since SMR is relatively new, industry standards for outputs have not yet been developed. It is important to understand the vendor’s policies and capacities for standard and custom reporting. Relevant questions include:

Does the company offer a full-service model of data collection, analysis and presentation or do they offer a self-service tool such as a portal?
In cases where the vendor offers full-service reporting and presentation, what substantive outputs may be expected? What technical explanation and reporting may be expected (e.g., a technical appendix)?
Are the SMR analyses incorporated with traditional types of marketing research and does the company have expertise doing so?
Does the provider offer standardized or customized tools?
How often are outputs updated and/or delivered?

#12. What is the process for gathering data?

Like other forms of opinion research, a wide variety of approaches exist for the implementation of SMR. It is important to understand the company policies undertaken. Relevant questions include:

Does the company gather its own data or is a data collection vendor used?
How many Web sites are crawled and how are those Web sites selected?
Does the company seek out permission-based relationships with the sites they crawl?
Does the company honor the electronic privacy notifications of individual Web sites?

#13. What data quality processes are implemented in each stage of the SMR?

What quality and validation protocols have been adopted and implemented to safeguard the quality of the research at each stage of the process? Are there validation processes in place for initial data collection, scoring and coding, etc.? Does the organization collect and retain information at the initial stages for validation purposes while removing/anonymizing data for reporting purposes?

#14. Does the company provide sentiment scoring?

Sentiment scoring is a process of assigning a positive or negative emotion to a conversation. Some vendors may provide strictly positive or negative emotions, while others may assign a continuum ranging from positive to neutral, to negative. If the vendor provides sentiment scoring, is the process an internal proprietary method, a third party purchased product, or some combination of the two? How is the sentiment scored (e.g., dictionary, bayesian, manually)?

#15. If sentiment scoring is provided, what is the process for validating results?

Simple and commonly-used systems of sentiment validation may prove to be inadequate. More rigorous approaches should be used, specifically blinded methods. For example:

For automated systems, researchers should receive a list of uncoded conversations and then code them manually. The manual codes should then be matched back and compared to the automated codes to derive a percentage match (i.e., validation coefficient).

For manual systems, two unique raters should independently code conversations. A validation coefficient may be derived from a comparison of the two outputs.

The above processes are two relatively simple examples of validation systems. More complicated calculations are available, but their use should be weighed according to the capacity of stakeholders to understand the meaning and method of the technique.

Language constantly changes and evolves due to new and lapsed slang, terminology, and speech patterns. As such, simple systems of sentiment validation may prove to be inadequate. When conducting SMR, rigorous and constantly monitored approaches to sentiment analysis are most appropriate.

#16. What, if any, methods are used for determining the geography associated with the data?

Demographic and geographic information can often be an important and meaningful element for research and validation purposes. When considering SMR, what geographic information is available and how precise is the information (e.g., city or town, region, country, unknown)? What types of demographic data are available (e.g., age, gender, income, education)?

Researchers must take care to specify the methodology and sample size associated with the information. Inferred methods (based on Web site sources or language) may be associated with large sample sizes but have low validity. On the other hand, precise information is currently only available for an extremely tiny percentage of conversations and therefore often has insufficient generalizability.

The “Top 16 Questions” presented in this guide represent the core matters of importance to the research field with respect to social media research. They include issues of reliability, execution, interaction with other kinds of research, ethics and legal compliance, data quality, process, and outputs.

Importantly, the 16 questions in this document do not stand as the only ones the opinion research profession needs to address, nor do they take the place of standards of practice. Instead, they provide a starting point for experts and professionals to debate and discuss development toward this goal. As in any profession, a reasonable consensus should be reached in order to validly define and represent an industry standard of best practice. It is the goal of the Marketing Research Association that this document be widely distributed and contribute as such.

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The SAGE Handbook of Social Media Research Methods

By: Luke Sloan & Anabel Quan-Haase
Publisher: SAGE Publications Ltd
Publication year: 2016
Online pub date: February 02, 2018
Discipline: Communication and Media Studies
Methods: Social media research , Big data
DOI: https:// doi. org/10.4135/9781473983847
Keywords: media research , social media , social media , social networks , social research , Twitter , Twitter Show all Show less
Print ISBN: 9781473916326
Online ISBN: 9781473983847
Buy the book icon link

Subject index

The SAGE Handbook of Social Media Research Methods offers a step-by-step guide to overcoming the challenges inherent in research projects that deal with 'big and broad data', from the formulation of research questions through to the interpretation of findings. The handbook includes chapters on specific social media platforms such as Twitter, Sina Weibo and Instagram, as well as a series of critical chapters. The holistic approach is organised into the following sections: Conceptualising & Designing Social Media Research Collection & Storage Qualitative Approaches to Social Media Data Quantitative Approaches to Social Media Data Diverse Approaches to Social Media Data Analytical Tools Social Media Platforms This handbook is the single most comprehensive resource for any scholar or graduate student embarking on a social media project.

Front Matter

List of Figures
List of Tables
Notes on the Editors and Contributors
Acknowledgements
Chapter 1 | Introduction to the Handbook of Social Media Research Methods: Goals, Challenges and Innovations
Chapter 2 | What is Social Media and What Questions Can Social Media Research Help Us Answer?
Chapter 3 | Big Data – Hype or Revolution?
Chapter 4 | Building Interdisciplinary Social Media Research Teams: Motivations, Challenges, and Policy Frameworks
Chapter 5 | Social Media Users’ Views on the Ethics of Social Media Research
Chapter 6 | The Role of Online Reputation Management, Trolling, and Personality Traits in the Crafting of the Virtual Self on Social Media
Chapter 7 | Social Science ‘Lite’? Deriving Demographic Proxies from Twitter
Chapter 8 | Think Before You Collect: Setting Up a Data Collection Approach for Social Media Studies
Chapter 9 | Overview – The Social Media Data Processing Pipeline
Chapter 10 | The Role of APIs in Data Sampling from Social Media
Chapter 11 | Data Storage, Curation and Preservation
Chapter 12 | Using Social Media in Data Collection: Designing Studies with the Qualitative E-Research Framework
Chapter 13 | Small Data, Thick Data: Thickening Strategies for Trace-based Social Media Research
Chapter 14 | Visuality in Social Media: Researching Images, Circulations and Practices
Chapter 15 | Coding of Non-Text Data
Chapter 16 | Twitter as Method: Using Twitter as a Tool to Conduct Research
Chapter 17 | Small Stories Research: A Narrative Paradigm for the Analysis of Social Media
Chapter 18 | Geospatial Analysis
Chapter 19 | Pragmatics of Network Centrality
Chapter 20 | Predictive Analytics with Social Media Data
Chapter 21 | Deception Detection and Rumor Debunking for Social Media
Chapter 22 | From Site-specificity to Hyper-locality: Performances of Place in Social Media
Chapter 23 | Analyzing Social Media Data and Other Data Sources: A Methodological Overview
Chapter 24 | Listening to Social Rhythms: Exploring Logged Interactional Data Through Sonification
Chapter 25 | Innovative Social Location-aware Services for Mobile Phones
Chapter 26 | COSMOS: The Collaborative On-line Social Media Observatory
Chapter 27 | Social Lab: An ‘Open Source Facebook’
Chapter 28 | R for Social Media Analysis
Chapter 29 | GATE: An Open-source NLP Toolkit for Mining Social Media
Chapter 30 | A How-to for Using Netlytic to Collect and Analyze Social Media Data: A Case Study of the Use of Twitter During the 2014 Euromaidan Revolution in Ukraine
Chapter 31 | Theme Detection in Social Media
Chapter 32 | Sentiment Analysis
Chapter 33 | The Ontology of Tweets: Mixed-Method Approaches to the Study of Twitter
Chapter 34 | Instagram
Chapter 35 | Weibo
Chapter 36 | Foursquare
Chapter 37 | Facebook as a Research Tool in the Social and Computer Sciences
Chapter 38 | Big Data and Political Science: The Case of VKontakte and the 2014 Euromaidan Revolution in Ukraine
Chapter 39 | A Retrospective on State of the Art Social Media Research Methods: Ethical Decisions, Big-small Data Rivalries and the Spectre of the 6Vs

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Open access
Published: 01 July 2020

The effect of social media on well-being differs from adolescent to adolescent

Ine Beyens ORCID: orcid.org/0000-0001-7023-867X 1 ,
J. Loes Pouwels ORCID: orcid.org/0000-0002-9586-392X 1 ,
Irene I. van Driel ORCID: orcid.org/0000-0002-7810-9677 1 ,
Loes Keijsers ORCID: orcid.org/0000-0001-8580-6000 2 &
Patti M. Valkenburg ORCID: orcid.org/0000-0003-0477-8429 1

Scientific Reports volume 10 , Article number: 10763 ( 2020 ) Cite this article

115k Accesses

196 Citations

118 Altmetric

Metrics details

Human behaviour

The question whether social media use benefits or undermines adolescents’ well-being is an important societal concern. Previous empirical studies have mostly established across-the-board effects among (sub)populations of adolescents. As a result, it is still an open question whether the effects are unique for each individual adolescent. We sampled adolescents’ experiences six times per day for one week to quantify differences in their susceptibility to the effects of social media on their momentary affective well-being. Rigorous analyses of 2,155 real-time assessments showed that the association between social media use and affective well-being differs strongly across adolescents: While 44% did not feel better or worse after passive social media use, 46% felt better, and 10% felt worse. Our results imply that person-specific effects can no longer be ignored in research, as well as in prevention and intervention programs.

Some socially poor but also some socially rich adolescents feel closer to their friends after using social media

J. Loes Pouwels, Patti M. Valkenburg, … Loes Keijsers

questions to research about social media

Associations between youth’s daily social media use and well-being are mediated by upward comparisons

Andrea Irmer & Florian Schmiedek

Variation in social media sensitivity across people and contexts

Sumer S. Vaid, Lara Kroencke, … Gabriella M. Harari

Introduction

Ever since the introduction of social media, such as Facebook and Instagram, researchers have been studying whether the use of such media may affect adolescents’ well-being. These studies have typically reported mixed findings, yielding either small negative, small positive, or no effects of the time spent using social media on different indicators of well-being, such as life satisfaction and depressive symptoms (for recent reviews, see for example 1 , 2 , 3 , 4 , 5 ). Most of these studies have focused on between-person associations, examining whether adolescents who use social media more (or less) often than their peers experience lower (or higher) levels of well-being than these peers. While such between-person studies are valuable in their own right, several scholars 6 , 7 have recently called for studies that investigate within-person associations to understand whether an increase in an adolescent’s social media use is associated with an increase or decrease in that adolescent’s well-being. The current study aims to respond to this call by investigating associations between social media use and well-being within single adolescents across multiple points in time 8 , 9 , 10 .

Person-specific effects

To our knowledge, four recent studies have investigated within-person associations of social media use with different indicators of adolescent well-being (i.e., life satisfaction, depression), again with mixed results 6 , 11 , 12 , 13 . Orben and colleagues 6 found a small negative reciprocal within-person association between the time spent using social media and life satisfaction. Likewise, Boers and colleagues 12 found a small within-person association between social media use and increased depressive symptoms. Finally, Coyne and colleagues 11 and Jensen and colleagues 13 did not find any evidence for within-person associations between social media use and depression.

Earlier studies that investigated within-person associations of social media use with indicators of well-being have all only reported average effect sizes. However, it is possible, or even plausible, that these average within-person effects may have been small and nonsignificant because they result from sizeable heterogeneity in adolescents’ susceptibility to the effects of social media use on well-being (see 14 , 15 ). After all, an average within-person effect size can be considered an aggregate of numerous individual within-person effect sizes that range from highly positive to highly negative.

Some within-person studies have sought to understand adolescents’ differential susceptibility to the effects of social media by investigating differences between subgroups. For instance, they have investigated the moderating role of sex to compare the effects of social media on boys versus girls 6 , 11 . However, such a group-differential approach, in which potential differences in susceptibility are conceptualized by group-level moderators (e.g., gender, age) does not provide insights into more fine-grained differences at the level of the single individual 16 . After all, while girls and boys each represent a homogenous group in terms of sex, they may each differ on a wide array of other factors.

As such, although worthwhile, the average within-person effects of social media on well-being obtained in previous studies may have been small or non-significant because they are diluted across a highly heterogeneous population (or sub-population) of adolescents 14 , 15 . In line with the proposition of media effects theories that each adolescent may have a unique susceptibility to the effects of social media 17 , a viable explanation for the small and inconsistent findings in earlier studies may be that the effect of social media differs from adolescent to adolescent. The aim of the current study is to investigate this hypothesis and to obtain a better understanding of adolescents’ unique susceptibility to the effects of social media on their affective well-being.

Social media and affective well-being

Within-person studies have provided important insights into the associations of social media use with cognitive well-being (e.g., life satisfaction 6 ), which refers to adolescents’ cognitive judgment of how satisfied they are with their life 18 . However, the associations of social media use with adolescents’ affective well-being (i.e., adolescents’ affective evaluations of their moods and emotions 18 ) are still unknown. In addition, while earlier within-person studies have focused on associations with trait-like conceptualizations of well-being 11 , 12 , 13 , that is, adolescents’ average well-being across specific time periods 18 , there is a lack of studies that focus on well-being as a momentary affective state. Therefore, we extend previous research by examining the association between adolescents’ social media use and their momentary affective well-being. Like earlier experience sampling (ESM) studies among adults 19 , 20 , we measured adolescents’ momentary affective well-being with a single item. Adolescents’ momentary affective well-being was defined as their current feelings of happiness, a commonly used question to measure well-being 21 , 22 , which has high convergent validity, as evidenced by the strong correlations with the presence of positive affect and absence of negative affect.

To assess adolescents’ momentary affective well-being (henceforth referred to as well-being), we conducted a week-long ESM study among 63 middle adolescents ages 14 and 15. Six times a day, adolescents were asked to complete a survey using their own mobile phone, covering 42 assessments per adolescent, assessing their affective well-being and social media use. In total, adolescents completed 2,155 assessments (83.2% average compliance).

We focused on middle adolescence, since this is the period in life characterized by most significant fluctuations in well-being 23 , 24 . Also, in comparison to early and late adolescents, middle adolescents are more sensitive to reactions from peers and have a strong tendency to compare themselves with others on social media and beyond. Because middle adolescents typically use different social media platforms, in a complementary way 25 , 26 , 27 , each adolescent reported on his/her use of the three social media platforms that s/he used most frequently out of the five most popular social media platforms among adolescents: WhatsApp, followed by Instagram, Snapchat, YouTube, and, finally, the chat function of games 28 . In addition to investigating the association between overall social media use and well-being (i.e., the summed use of adolescents’ three most frequently used platforms), we examined the unique associations of the two most popular platforms, WhatsApp and Instagram 28 .

Like previous studies on social media use and well-being, we distinguished between active social media use (i.e., “activities that facilitate direct exchanges with others” 29 ) and passive social media use (i.e., “consuming information without direct exchanges” 29 ). Within-person studies among young adults have shown that passive but not active social media use predicts decreases in well-being 29 . Therefore, we examined the unique associations of adolescents’ overall active and passive social media use with their well-being, as well as active and passive use of Instagram and WhatsApp, specifically. We investigated categorical associations, that is, whether adolescents would feel better or worse if they had actively or passively used social media. And we investigated dose–response associations to understand whether adolescents’ well-being would change as a function of the time they had spent actively or passively using social media.

The hypotheses and the design, sampling and analysis plan were preregistered prior to data collection and are available on the Open Science Framework, along with the code used in the analyses ( https://osf.io/nhks2 ). For details about the design of the study and analysis approach, see Methods.

In more than half of all assessments (68.17%), adolescents had used social media (i.e., one or more of their three favorite social media platforms), either in an active or passive way. Instagram (50.90%) and WhatsApp (53.52%) were used in half of all assessments. Passive use of social media (66.21% of all assessments) was more common than active use (50.86%), both on Instagram (48.48% vs. 20.79%) and WhatsApp (51.25% vs. 40.07%).

Strong positive between-person correlations were found between the duration of active and passive social media use (overall: r = 0.69, p < 0.001; Instagram: r = 0.38, p < 0.01; WhatsApp: r = 0.85, p < 0.001): Adolescents who had spent more time actively using social media than their peers, had also spent more time passively using social media than their peers. Likewise, strong positive within-person correlations were found between the duration of active and passive social media use (overall: r = 0.63, p < 0.001; Instagram: r = 0.37, p < 0.001; WhatsApp: r = 0.57, p < 0.001): The more time an adolescent had spent actively using social media at a certain moment, the more time s/he had also spent passively using social media at that moment.

Table 1 displays the average number of minutes that adolescents had spent using social media in the past hour at each assessment, and the zero-order between- and within-person correlations between the duration of social media use and well-being. At the between-person level, the duration of active and passive social media use was not associated with well-being: Adolescents who had spent more time actively or passively using social media than their peers did not report significantly higher or lower levels of well-being than their peers. At the within-person level, significant but weak positive correlations were found between the duration of active and passive overall social media use and well-being. This indicates that adolescents felt somewhat better at moments when they had spent more time actively or passively using social media (overall), compared to moments when they had spent less time actively or passively using social media. When looking at specific platforms, a positive correlation was only found for passive WhatsApp use, but not for active WhatsApp use, and not for active and passive Instagram use.

Average and person-specific effects

The within-person associations of social media use with well-being and differences in these associations were tested in a series of multilevel models. We ran separate models for overall social media use (i.e., active use and passive use of adolescents’ three favorite social media platforms, see Table 2 ), Instagram use (see Table 3 ), and WhatsApp use (see Table 4 ). In a first step we examined the average categorical associations for each of these three social media uses using fixed effects models (Models 1A, 3A, and 5A) to investigate whether, on average, adolescents would feel better or worse at moments when they had used social media compared to moments when they had not (i.e., categorical predictors: active use versus no active use, and passive use versus no passive use). In a second step, we examined heterogeneity in the within-person categorical associations by adding random slopes to the fixed effects models (Models 1B, 3B, and 5B). Next, we examined the average dose–response associations using fixed effects models (Models 2A, 4A, and 6A), to investigate whether, on average, adolescents would feel better or worse when they had spent more time using social media (i.e., continuous predictors: duration of active use and duration of passive use). Finally, we examined heterogeneity in the within-person dose–response associations by adding random slopes to the fixed effects models (Models 2B, 4B, and 6B).

Overall social media use.

The model with the categorical predictors (see Table 2 ; Model 1A) showed that, on average, there was no association between overall use and well-being: Adolescents’ well-being did not increase or decrease at moments when they had used social media, either in a passive or active way. However, evidence was found that the association of passive (but not active) social media use with well-being differed from adolescent to adolescent (Model 1B), with effect sizes ranging from − 0.24 to 0.68. For 44.26% of the adolescents the association was non-existent to small (− 0.10 < r < 0.10). However, for 45.90% of the adolescents there was a weak (0.10 < r < 0.20; 8.20%), moderate (0.20 < r < 0.30; 22.95%) or even strong positive ( r ≥ 0.30; 14.75%) association between overall passive social media use and well-being, and for almost one in ten (9.84%) adolescents there was a weak (− 0.20 < r < − 0.10; 6.56%) or moderate negative (− 0.30 < r < − 0.20; 3.28%) association.

The model with continuous predictors (Model 2A) showed that, on average, there was a significant dose–response association for active use. At moments when adolescents had used social media, the time they spent actively (but not passively) using social media was positively associated with well-being: Adolescents felt better at moments when they had spent more time sending messages, posting, or sharing something on social media. The associations of the time spent actively and passively using social media with well-being did not differ across adolescents (Model 2B).

Instagram use

As shown in Model 3A in Table 3 , on average, there was a significant categorical association between passive (but not active) Instagram use and well-being: Adolescents experienced an increase in well-being at moments when they had passively used Instagram (i.e., viewing posts/stories of others). Adolescents did not experience an increase or decrease in well-being when they had actively used Instagram. The associations of passive and active Instagram use with well-being did not differ across adolescents (Model 3B).

On average, no significant dose–response association was found for Instagram use (Model 4A): At moments when adolescents had used Instagram, the time adolescents spent using Instagram (either actively or passively) was not associated with their well-being. However, evidence was found that the association of the time spent passively using Instagram differed from adolescent to adolescent (Model 4B), with effect sizes ranging from − 0.48 to 0.27. For most adolescents (73.91%) the association was non-existent to small (− 0.10 < r < 0.10), but for almost one in five adolescents (17.39%) there was a weak (0.10 < r < 0.20; 10.87%) or moderate (0.20 < r < 0.30; 6.52%) positive association, and for almost one in ten adolescents (8.70%) there was a weak (− 0.20 < r < − 0.10; 2.17%), moderate (− 0.30 < r < − 0.20; 4.35%), or strong ( r ≤ − 0.30; 2.17%) negative association. Figure 1 illustrates these differences in the dose–response associations.

The dose–response association between passive Instagram use (in minutes per hour) and affective well-being for each individual adolescent (n = 46). Red lines represent significant negative within-person associations, green lines represent significant positive within-person associations, and gray lines represent non-significant within-person associations. A graph was created for each participant who had completed at least 10 assessments. A total of 13 participants were excluded because they had completed less than 10 assessments of passive Instagram use. In addition, one participant was excluded because no graph could be computed, since this participant's passive Instagram use was constant across assessments.

WhatsApp use

As shown in Model 5A in Table 4 , just as for Instagram, we found that, on average, there was a significant categorical association between passive (but not active) WhatsApp use and well-being: Adolescents reported that they felt better at moments when they had passively used WhatsApp (i.e., read WhatsApp messages). For active WhatsApp use, no significant association was found. Also, in line with the results for Instagram use, no differences were found regarding the associations of active and passive WhatsApp use (Model 5B).

In addition, a significant dose–response association was found for passive (but not active) use (Model 6A). At moments when adolescents had used WhatsApp, we found that, on average, the time adolescents spent passively using WhatsApp was positively associated with well-being: Adolescents felt better at moments when they had spent more time reading WhatsApp messages. The time spent actively using WhatsApp was not associated with well-being. No differences were found in the dose–response associations of active and passive WhatsApp use (Model 6B).

This preregistered study investigated adolescents’ unique susceptibility to the effects of social media. We found that the associations of passive (but not active) social media use with well-being differed substantially from adolescent to adolescent, with effect sizes ranging from moderately negative (− 0.24) to strongly positive (0.68). While 44.26% of adolescents did not feel better or worse if they had passively used social media, 45.90% felt better, and a small group felt worse (9.84%). In addition, for Instagram the majority of adolescents (73.91%) did not feel better or worse when they had spent more time viewing post or stories of others, whereas some felt better (17.39%), and others (8.70%) felt worse.

These findings have important implications for social media effects research, and media effects research more generally. For decades, researchers have argued that people differ in their susceptibility to the effects of media 17 , leading to numerous investigations of such differential susceptibility. These investigations have typically focused on moderators, based on variables such as sex, age, or personality. Yet, over the years, studies have shown that such moderators appear to have little power to explain how individuals differ in their susceptibility to media effects, probably because a group-differential approach does not account for the possibility that media users may differ across a range of factors, that are not captured by only one (or a few) investigated moderator variables.

By providing insights into each individual’s unique susceptibility, the findings of this study provide an explanation as to why, up until now, most media effects research has only found small effects. We found that the majority of adolescents do not experience any short-term changes in well-being related to their social media use. And if they do experience any changes, these are more often positive than negative. Because only small subsets of adolescents experience small to moderate changes in well-being, the true effects of social media reported in previous studies have probably been diluted across heterogeneous samples of individuals that differ in their susceptibility to media effects (also see 30 ). Several scholars have noted that overall effect sizes may mask more subtle individual differences 14 , 15 , which may explain why previous studies have typically reported small or no effects of social media on well-being or indicators of well-being 6 , 11 , 12 , 13 . The current study seems to confirm this assumption, by showing that while the overall effect sizes are small at best, the person-specific effect sizes vary considerably, from tiny and small to moderate and strong.

As called upon by other scholars 5 , 31 , we disentangled the associations of active and passive use of social media. Research among young adults found that passive (but not active) social media use is associated with lower levels of affective well-being 29 . In line with these findings, the current study shows that active and passive use yielded different associations with adolescents’ affective well-being. Interestingly though, in contrast to previous findings among adults, our study showed that, on average, passive use of Instagram and WhatsApp seemed to enhance rather than decrease adolescents’ well-being. This discrepancy in findings may be attributed to the fact that different mechanisms might be involved. Verduyn and colleagues 29 found that passive use of Facebook undermines adults’ well-being by enhancing envy, which may also explain the decreases in well-being found in our study among a small group of adolescents. Yet, adolescents who felt better by passively using Instagram and WhatsApp, might have felt so because they experienced enjoyment. After all, adolescents often seek positive content on social media, such as humorous posts or memes 32 . Also, research has shown that adolescents mainly receive positive feedback on social media 33 . Hence, their passive Instagram and WhatsApp use may involve the reading of positive feedback, which may explain the increases in well-being.

Overall, the time spent passively using WhatsApp improved adolescents’ well-being. This did not differ from adolescent to adolescent. However, the associations of the time spent passively using Instagram with well-being did differ from adolescent to adolescent. This discrepancy suggests that not all social media uses yield person-specific effects on well-being. A possible explanation may be that adolescents’ responses to WhatsApp are more homogenous than those to Instagram. WhatsApp is a more private platform, which is mostly used for one-to-one communication with friends and acquaintances 26 . Instagram, in contrast, is a more public platform, which allows its users to follow a diverse set of people, ranging from best friends to singers, actors, and influencers 28 , and to engage in intimate communication as well as self-presentation and social comparison. Such diverse uses could lead to more varied, or even opposing responses, such as envy versus inspiration.

Limitations and directions for future research

The current study extends our understanding of differential susceptibility to media effects, by revealing that the effect of social media use on well-being differs from adolescent to adolescent. The findings confirm our assumption that among the great majority of adolescents, social media use is unrelated to well-being, but that among a small subset, social media use is either related to decreases or increases in well-being. It must be noted, however, that participants in this study felt relatively happy, overall. Studies with more vulnerable samples, consisting of clinical samples or youth with lower social-emotional well-being may elicit different patterns of effects 27 . Also, the current study focused on affective well-being, operationalized as happiness. It is plausible that social media use relates differently with other types of well-being, such as cognitive well-being. An important next step is to identify which adolescents are particularly susceptible to experience declines in well-being. It is conceivable, for instance, that the few adolescents who feel worse when they use social media are the ones who receive negative feedback on social media 33 .

In addition, future ESM studies into the effects of social media should attempt to include one or more follow-up measures to improve our knowledge of the longer-term influence of social media use on affective well-being. While a week-long ESM is very common and applied in most earlier ESM studies 34 , a week is only a snapshot of adolescent development. Research is needed that investigates whether the associations of social media use with adolescents’ momentary affective well-being may cumulate into long-lasting consequences. Such investigations could help clarify whether adolescents who feel bad in the short term would experience more negative consequences in the long term, and whether adolescents who feel better would be more resistant to developing long-term negative consequences. And while most adolescents do not seem to experience any short-term increases or decreases in well-being, more research is needed to investigate whether these adolescents may experience a longer-term impact of social media.

While the use of different platforms may be differently associated with well-being, different types of use may also yield different effects. Although the current study distinguished between active and passive use of social media, future research should further differentiate between different activities. For instance, because passive use entails many different activities, from reading private messages (e.g., WhatsApp messages, direct messages on Instagram) to browsing a public feed (e.g., scrolling through posts on Instagram), research is needed that explores the unique effects of passive public use and passive private use. Research that seeks to explore the nuances in adolescents’ susceptibility as well as the nuances in their social media use may truly improve our understanding of the effects of social media use.

Participants

Participants were recruited via a secondary school in the south of the Netherlands. Our preregistered sampling plan set a target sample size of 100 adolescents. We invited adolescents from six classrooms to participate in the study. The final sample consisted of 63 adolescents (i.e., 42% consent rate, which is comparable to other ESM studies among adolescents; see, for instance 35 , 36 ). Informed consent was obtained from all participants and their parents. On average, participants were 15 years old ( M = 15.12 years, SD = 0.51) and 54% were girls. All participants self-identified as Dutch, and 41.3% were enrolled in the prevocational secondary education track, 25.4% in the intermediate general secondary education track, and 33.3% in the academic preparatory education track.

The study was approved by the Ethics Review Board of the Faculty of Social and Behavioral Sciences at the University of Amsterdam and was performed in accordance with the guidelines formulated by the Ethics Review Board. The study consisted of two phases: A baseline survey and a personalized week-long experience sampling (ESM) study. In phase 1, researchers visited the school during school hours. Researchers informed the participants of the objective and procedure of the study and assured them that their responses would be treated confidentially. Participants were asked to sign the consent form. Next, participants completed a 15-min baseline survey. The baseline survey included questions about demographics and assessed which social media each adolescent used most frequently, allowing to personalize the social media questions presented during the ESM study in phase 2. After completing the baseline survey, participants were provided detailed instructions about phase 2.

In phase 2, which took place two and a half weeks after the baseline survey, a 7-day ESM study was conducted, following the guidelines for ESM studies provided by van Roekel and colleagues 34 . Aiming for at least 30 assessments per participant and based on an average compliance rate of 70 to 80% reported in earlier ESM studies among adolescents 34 , we asked each participant to complete a total of 42 ESM surveys (i.e., six 2-min surveys per day). Participants completed the surveys using their own mobile phone, on which the ESM software application Ethica Data was installed during the instruction session with the researchers (phase 1). Each 2-min survey consisted of 22 questions, which assessed adolescents’ well-being and social media use. Two open-ended questions were added to the final survey of the day, which asked about adolescents’ most pleasant and most unpleasant events of the day.

The ESM sampling scheme was semi-random, to allow for randomization and avoid structural patterns in well-being, while taking into account that adolescents were not allowed to use their phone during school time. The Ethica Data app was programmed to generate six beep notifications per day at random time points within a fixed time interval that was tailored to the school’s schedule: before school time (1 beep), during school breaks (2 beeps), and after school time (3 beeps). During the weekend, the beeps were generated during the morning (1 beep), afternoon (3 beeps), and evening (2 beeps). To maximize compliance, a 30-min time window was provided to complete each survey. This time window was extended to one hour for the first survey (morning) and two hours for the final survey (evening) to account for travel time to school and time spent on evening activities. The average compliance rate was 83.2%. A total of 2,155 ESM assessments were collected: Participants completed an average of 34.83 surveys ( SD = 4.91) on a total of 42 surveys, which is high compared to previous ESM studies among adolescents 34 .

The questions of the ESM study were personalized based on the responses to the baseline survey. During the ESM study, each participant reported on his/her use of three different social media platforms: WhatsApp and either Instagram, Snapchat, YouTube, and/or the chat function of games (i.e., the most popular social media platforms among adolescents 28 ). Questions about Instagram and WhatsApp use were only included if the participant had indicated in the baseline survey that s/he used these platforms at least once a week. If a participant had indicated that s/he used Instagram or WhatsApp (or both) less than once a week, s/he was asked to report on the use of Snapchat, YouTube, or the chat function of games, depending on what platform s/he used at least once a week. In addition to Instagram and WhatsApp, questions were asked about a third platform, that was selected based on how frequently the participant used Snapchat, YouTube, or the chat function of games (i.e., at least once a week). This resulted in five different combinations of three platforms: Instagram, WhatsApp, and Snapchat (47 participants); Instagram, WhatsApp, and YouTube (11 participants); Instagram, WhatsApp, and chatting via games (2 participants); WhatsApp, Snapchat, and YouTube (1 participant); and WhatsApp, YouTube, and chatting via games (2 participants).

Frequency of social media use

In the baseline survey, participants were asked to indicate how often they used and checked Instagram, WhatsApp, Snapchat, YouTube, and the chat function of games, using response options ranging from 1 ( never ) to 7 ( more than 12 times per day ). These platforms are the five most popular platforms among Dutch 14- and 15-year-olds 28 . Participants’ responses were used to select the three social media platforms that were assessed in the personalized ESM study.

Duration of social media use

In the ESM study, duration of active and passive social media use was measured by asking participants how much time in the past hour they had spent actively and passively using each of the three platforms that were included in the personalized ESM surveys. Response options ranged from 0 to 60 min , with 5-min intervals. To measure active Instagram use, participants indicated how much time in the past hour they had spent (a) “posting on your feed or sharing something in your story on Instagram” and (b) “sending direct messages/chatting on Instagram.” These two items were summed to create the variable duration of active Instagram use. Sum scores exceeding 60 min (only 0.52% of all assessments) were recoded to 60 min. To measure duration of passive Instagram use, participants indicated how much time in the past hour they had spent “viewing posts/stories of others on Instagram.” To measure the use of WhatsApp, Snapchat, YouTube and game-based chatting, we asked participants how much time they had spent “sending WhatsApp messages” (active use) and “reading WhatsApp messages” (passive use); “sending snaps/messages or sharing something in your story on Snapchat” (active use) and “viewing snaps/stories/messages from others on Snapchat” (passive use); “posting YouTube clips” (active use) and “watching YouTube clips” (passive use); “sending messages via the chat function of a game/games” (active use) and “reading messages via the chat function of a game/games” (passive use). Duration of active and passive overall social media use were created by summing the responses across the three social media platforms for active and passive use, respectively. Sum scores exceeding 60 min (2.13% of all assessments for active overall use; 2.90% for passive overall use) were recoded to 60 min. The duration variables were used to investigate whether the time spent actively or passively using social media was associated with well-being (dose–response associations).

Use/no use of social media

Based on the duration variables, we created six dummy variables, one for active and one for passive overall social media use, one for active and one for passive Instagram use, and one for active and one for passive WhatsApp use (0 = no active use and 1 = active use , and 0 = no passive use and 1 = passive use , respectively). These dummy variables were used to investigate whether the use of social media, irrespective of the duration of use, was associated with well-being (categorical associations).

Consistent with previous ESM studies 19 , 20 , we measured affective well-being using one item, asking “How happy do you feel right now?” at each assessment. Adolescents indicated their response to the question using a 7-point scale ranging from 1 ( not at all ) to 7 ( completely ), with 4 ( a little ) as the midpoint. Convergent validity of this item was established in a separate pilot ESM study among 30 adolescents conducted by the research team of the fourth author: The affective well-being item was strongly correlated with the presence of positive affect and absence of negative affect (assessed by a 10-item positive and negative affect schedule for children; PANAS-C) at both the between-person (positive affect: r = 0.88, p < 0.001; negative affect: r = − 0.62, p < 0.001) and within-person level (positive affect: r = 0.74, p < 0.001; negative affect: r = − 0.58, p < 0.001).

Statistical analyses

Before conducting the analyses, several validation checks were performed (see 34 ). First, we aimed to only include participants in the analyses who had completed more than 33% of all ESM assessments (i.e., at least 14 assessments). Next, we screened participants’ responses to the open questions for unserious responses (e.g., gross comments, jokes). And finally, we inspected time series plots for patterns in answering tendencies. Since all participants completed more than 33% of all ESM assessments, and no inappropriate responses or low-quality data patterns were detected, all participants were included in the analyses.

Following our preregistered analysis plan, we tested the proposed associations in a series of multilevel models. Before doing so, we tested the homoscedasticity and linearity assumptions for multilevel analyses 37 . Inspection of standardized residual plots indicated that the data met these assumptions (plots are available on OSF at https://osf.io/nhks2 ). We specified separate models for overall social media use, use of Instagram, and use of WhatsApp. To investigate to what extent adolescents’ well-being would vary depending on whether they had actively or passively used social media/Instagram/WhatsApp or not during the past hour (categorical associations), we tested models including the dummy variables as predictors (active use versus no active use, and passive use versus no passive use; models 1, 3, and 5). To investigate whether, at moments when adolescents had used social media/Instagram/WhatsApp during the past hour, their well-being would vary depending on the duration of social media/Instagram/WhatsApp use (dose–response associations), we tested models including the duration variables as predictors (duration of active use and duration of passive use; models 2, 4, and 6). In order to avoid negative skew in the duration variables, we only included assessments during which adolescents had used social media in the past hour (overall, Instagram, or WhatsApp, respectively), either actively or passively. All models included well-being as outcome variable. Since multilevel analyses allow to include all available data for each individual, no missing data were imputed and no data points were excluded.

We used a model building approach that involved three steps. In the first step, we estimated an intercept-only model to assess the relative amount of between- and within-person variance in affective well-being. We estimated a three-level model in which repeated momentary assessments (level 1) were nested within adolescents (level 2), who, in turn, were nested within classrooms (level 3). However, because the between-classroom variance in affective well-being was small (i.e., 0.4% of the variance was explained by differences between classes), we proceeded with estimating two-level (instead of three-level) models, with repeated momentary assessments (level 1) nested within adolescents (level 2).

In the second step, we assessed the within-person associations of well-being with (a) overall active and passive social media use (i.e., the total of the three platforms), (b) active and passive use of Instagram, and (c) active and passive use of WhatsApp, by adding fixed effects to the model (Models 1A-6A). To facilitate the interpretation of the associations and control for the effects of time, a covariate was added that controlled for the n th assessment of the study week (instead of the n th assessment of the day, as preregistered). This so-called detrending is helpful to interpret within-person associations as correlated fluctuations beyond other changes in social media use and well-being 38 . In order to obtain within-person estimates, we person-mean centered all predictors 38 . Significance of the fixed effects was determined using the Wald test.

In the third and final step, we assessed heterogeneity in the within-person associations by adding random slopes to the models (Models 1B-6B). Significance of the random slopes was determined by comparing the fit of the fixed effects model with the fit of the random effects model, by performing the Satorra-Bentler scaled chi-square test 39 and by comparing the Bayesian information criterion (BIC 40 ) and Akaike information criterion (AIC 41 ) of the models. When the random effects model had a significantly better fit than the fixed effects model (i.e., pointing at significant heterogeneity), variance components were inspected to investigate whether heterogeneity existed in the association of either active or passive use. Next, when evidence was found for significant heterogeneity, we computed person-specific effect sizes, based on the random effect models, to investigate what percentages of adolescents experienced better well-being, worse well-being, and no changes in well-being. In line with Keijsers and colleagues 42 we only included participants who had completed at least 10 assessments. In addition, for the dose–response associations, we constructed graphical representations of the person-specific slopes, based on the person-specific effect sizes, using the xyplot function from the lattice package in R 43 .

Three improvements were made to our original preregistered plan. First, rather than estimating the models with multilevel modelling in R 43 , we ran the preregistered models in Mplus 44 . Mplus provides standardized estimates for the fixed effects models, which offers insight into the effect sizes. This allowed us to compare the relative strength of the associations of passive versus active use with well-being. Second, instead of using the maximum likelihood estimator, we used the maximum likelihood estimator with robust standard errors (MLR), which are robust to non-normality. Sensitivity tests, uploaded on OSF ( https://osf.io/nhks2 ), indicated that the results were almost identical across the two software packages and estimation approaches. Third, to improve the interpretation of the results and make the scales of the duration measures of social media use and well-being more comparable, we transformed the social media duration scores (0 to 60 min) into scales running from 0 to 6, so that an increase of 1 unit reflects 10 min of social media use. The model estimates were unaffected by this transformation.

Reporting summary

Further information on the research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

The dataset generated and analysed during the current study is available in Figshare 45 . The preregistration of the design, sampling and analysis plan, and the analysis scripts used to analyse the data for this paper are available online on the Open Science Framework website ( https://osf.io/nhks2 ).

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Acknowledgements

This study was funded by the NWO Spinoza Prize and the Gravitation grant (NWO Grant 024.001.003; Consortium on Individual Development) awarded to P.M.V. by the Dutch Research Council (NWO). Additional funding was received from the VIDI grant (NWO VIDI Grant 452.17.011) awarded to L.K. by the Dutch Research Council (NWO). The authors would like to thank Savannah Boele (Tilburg University) for providing her pilot ESM results.

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I.B., J.L.P., I.I.v.D., L.K., and P.M.V. designed the study; I.B., J.L.P., and I.I.v.D. collected the data; I.B., J.L.P., and L.K. analyzed the data; and I.B., J.L.P., I.I.v.D., L.K., and P.M.V. contributed to writing and reviewing the manuscript.

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Beyens, I., Pouwels, J.L., van Driel, I.I. et al. The effect of social media on well-being differs from adolescent to adolescent. Sci Rep 10 , 10763 (2020). https://doi.org/10.1038/s41598-020-67727-7

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10 Research Question Examples to Guide your Research Project

Published on October 30, 2022 by Shona McCombes . Revised on October 19, 2023.

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Tackling misinformation: What researchers could do with social media data

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Written by Irene V. Pasquetto, Briony Swire-Thompson, Michelle A. Amazeen, Fabrício Benevenuto, Nadia M. Brashier, Robert M. Bond, Lia C. Bozarth, Ceren Budak, Ullrich K. H. Ecker, Lisa K. Fazio, Emilio Ferrara, Andrew J. Flanagin, Alessandro Flammini, Deen Freelon, Nir Grinberg, Ralph Hertwig, Kathleen Hall Jamieson, Kenneth Joseph, Jason J. Jones, R. Kelly Garrett, Daniel Kreiss, Shannon McGregor, Jasmine McNealy, Drew Margolin, Alice Marwick, FiIippo Menczer, Miriam J. Metzger, Seungahn Nah, Stephan Lewandowsky, Philipp Lorenz-Spreen, Pablo Ortellado, Gordon Pennycook, Ethan Porter, David G. Rand, Ronald E. Robertson, Francesca Tripodi, Soroush Vosoughi, Chris Vargo, Onur Varol, Brian E. Weeks, John Wihbey, Thomas J. Wood, & Kai-Cheng Yang

Introduction

Authors: Irene V. Pasquetto (1), Briony Swire-Thompson (2) Affiliations: (1) School of Information, University of Michigan, USA; Shorenstein Center on Media, Politics and Public Policy, Harvard Kennedy School, USA (2) Network Science Institute, Northeastern University, USA; Institute of Quantitative Social Science, Harvard University, USA

Social media platforms rarely provide data to misinformation researchers. This is problematic as platforms play a major role in the diffusion and amplification of mis- and disinformation narratives. Scientists are often left working with partial or biased data and must rush to archive relevant data as soon as it appears on the platforms, before it is suddenly and permanently removed by deplatforming operations. Alternatively, scientists have conducted off-platform laboratory research that approximates social media use. While this can provide useful insights, this approach can have severely limited external validity (though see Munger, 2017; Pennycook et al. 2020). For researchers in the field of misinformation, emphasizing the necessity of establishing better collaborations with social media platforms has become routine. In-lab studies and off-platform investigations can only take us so far. Increased data access would enable researchers to perform studies on a broader scale, allow for improved characterization of misinformation in real-world contexts, and facilitate the testing of interventions to prevent the spread of misinformation. The current paper highlights 15 opinions from researchers detailing these possibilities and describes research that could hypothetically be conducted if social media data were more readily available. As scientists, our findings are only as good as the dataset at our disposal, and with the current misinformation crisis, it is urgent that we have access to real-world data where misinformation is wreaking the most havoc.

While new collaborative efforts are gradually emerging (e.g., Clegg, 2020; Mervis, 2020), they remain scarce and unevenly distributed across research communities and disciplines. Platforms periodically fund research initiatives on mis- and disinformation, but these rarely include increased access to data and algorithmic models. Most importantly, in these kinds of collaborations, intellectual freedom is easily limited by the fact that the overarching scope of the research is not defined by the researchers, but by the platforms themselves. In the rare case data sharing is a possibility, negotiations have been slow for several reasons, including platforms’ concerns over protecting their brands and reputation, and ethical and legal issues of privacy and data security on a grand scale (Bechmann & Kim, 2020; Olteanu et al., 2019). However, these barriers are not insurmountable (Moreno et al., 2013; Lazer et al. 2020). For instance, establishing a mechanism by which users can actively consent to various research studies, and potentially offering to make the data available to the participants themselves, would be a significant step forward (Donovan, 2020).

We invited misinformation researchers to write a 250-word commentary about the research that they would hypothetically conduct if they had access to consenting participants’ social media data. The excerpts below provide concrete examples of studies that misinformation researchers could conduct, if the community had better access to platforms’ data and processes. Based on the contents of the submission, we have grouped these brief excerpts into five areas that could be improved, and conclude with an excerpt regarding the importance of data sharing:

measurement and design,
who engages with misinformation and why,
unique datasets with increased validity,
disinformation campaigns,
interventions, and
the importance of data sharing.

While these excerpts are not comprehensive and may not be representative of the field as a whole, our hope is that this multi-authored piece will further the conversation regarding the establishment of more evenly distributed collaborations between researchers and platforms. Despite the challenges, on the other side of these negotiations are a vast array of potential discoveries that are needed by both the nascent field of misinformation as well as society.

I. Measurement and design

The need for impression data in misinformation research.

Author: Soroush Vosoughi Affiliation: Department of Computer Science, Dartmouth College, USA

One of the main challenges in studying misinformation on social media is the inability to get the true reach of the content that is being shared. There are two metrics that measure the reach of a piece of content being posted on social media: expressions and impressions. Expressions correspond to the people who engaged with the content (e.g., retweeted it or liked it), while impressions correspond to the people who read that content. While expression data can be used to map how misinformation spreads, the true impact of misinformation can only be measured using impression data. Expression data is usually made available by social media platforms; impression data, however, is kept hidden from researchers. If the social media platforms were to make fine-grained impression data (i.e., who read what, when) available, we would be able to measure the true reach of misinformation. This would allow us to study, amongst other things, the difference between posts containing misinformation that are read and shared to those that are read but not shared; and the difference between the people who read and share misinformation to those who read but do not share. This will shed light on some of the factors involved in people deciding whether to share content that contains misinformation, potentially allowing us to predict in advance the virality and the diffusion path of misinformation with much greater accuracy than is currently possible. Additionally, these findings can help devise more effective intervention strategies to dampen the spread of misinformation.

External randomized controlled trials (RCT) with no internal controls

Authors: Ethan Porter (1), Thomas J. Wood (2) Affiliations: (1) School of Media & Public Affairs, The George Washington University, USA, (2) Department of Political Science, Ohio State University, USA

The most important contribution social media companies could make to the study of misinformation would be to allow external researchers to regularly conduct randomized controlled trials on their platforms, without interference or involvement from the companies themselves. While randomized control trials (RCTs) are among the strongest tools in a researcher’s toolbox, prior collaborations between academics and social media companies have prohibited them. Some companies have allowed researchers to conduct experiments, but these opportunities have been limited and questions of conflict of interest may arise. What is needed is a rolling opportunity for researchers to conduct independent RCTs on the largest platforms. Whether a proposed RCT is allowed should not be left to the discretion of the companies, but instead determined by a group of outside ethical and legal specialists, similar to a university Institutional Review Board (IRB). This group would minimize conflicts of interest and ensure that any research conducted would adhere to the IRB principles of confidentiality and privacy. Given such a system, a wide range of questions would suddenly become possible to answer. What kinds of interventions are most effective at reducing an individual’s propensity to share misinformation? Does exposure to one’s political opponents or allies affect willingness to share misinformation? To what extent, if any, does revealing the source of factual interventions affect behavior? This would just be the tip of the iceberg. Answers would come via individual-level data gathered on the platforms themselves, thus offering immediate external validity. Both the scientific and public understanding of the challenges of—and potential solutions to—misinformation would be significantly enhanced as a result.

What does the public need from social media platforms to really study fake news?

Authors: Kenneth Joseph (1), Nir Grinberg (2), John Wihbey (3) Affiliations: (1) Department of Computer Science and Engineering, University at Buffalo, USA, (2) Department of Software and Information Systems Engineering, Ben-Gurion University, Israel, (3) School of Journalism and Ethics Institute, Northeastern University, USA

Social media platforms, to various degrees, already provide data for academic purposes. However, these data are often quite limited in their ability to answer critical research questions. Rather than ask “what would we do with platform data?” then, we here address the question, “what data and tools do we really need to make progress?” We identify five broad avenues of future collaboration between platforms and the academic community that will be a leap forward in public understanding of the usage and impacts of these platforms: (a) A framework for targeting academic-led experiments and survey to relevant populations (e.g., based on online user activity, profile information); (b) Information about individual-level exposure to (mis)information and the ways individuals interacted with that (mis)information; (c) Signals about message authenticity and the origination of actions taken on the platform (e.g. was this action likely taken via automated or human-like behavior?); (d) Transparent and up-to-date information about content curation and moderation by algorithms and company personnel, including political ads; and (e) broader data access to larger subsets of historical data and to a wider range of platforms, especially in the form of well-behaved APIs for Instagram, TikTok, WhatsApp, and YouTube. Forming these tighter collaborations raises important questions about privacy and trust, but finding solutions to these issues may be in the public’s best interest if we as a society were to understand the full gravity of the post-truth trends.

II. Who engages with misinformation and why

Understanding how communication about misinformation can help to combat it.

Authors: Miriam J. Metzger (1), Andrew J. Flanagin (1) Affiliations: (1) Department of Communication, University of California, Santa Barbara, USA

People spread misinformation by intentionally sharing it among their network contacts, and it is widely presumed that those sharing and receiving misinformation find it to be veracious. However, there are many reasons that people may share misinformation. For example, although people might share information because they believe it to be true, they may also share misinformation for entertainment purposes, sarcastic reasons, or to challenge the misinformation. Under such circumstances, the alleged danger of fake news may be mitigated or, perhaps, even reversed. While it is possible to study motivations for sharing misinformation using standard social scientific methods, self-report data are subject to social desirability biases because people may be reluctant to admit believing or sharing misinformation for any reason. It is also difficult to study motivations on a large scale in a fashion that is representative of social media users. Ideally, we would like to collaborate with social media platforms to capture at scale (a) the communication surrounding the sharing of mis- and disinformation by both information sharers and receivers (e.g., captions, comments, emojis, annotations, etc.), (b) people’s network relationship data, and (c) users’ demographic information to analyze the extent to which people believe misinformation as they share or receive it, as mediated by user characteristics and the sharer-receiver relationship. Such data could be appropriately anonymized to protect user identities. Understanding what misinformation is shared with whom and why would help to develop effective means to combat the spread of misinformation and would offer pathways to design and test interventions to help users to interpret misinformation correctly.

Why do older adults share more misinformation? We need social media data to find out

Authors: Nadia M. Brashier (1), Lisa K. Fazio (2) Affiliations: (1) Department of Psychology, Harvard University, USA, (2) Department of Psychology and Human Development, Vanderbilt University, USA

Tackling the misinformation crisis requires a lifespan perspective, as older adults engage with (Grinberg et al., 2019) and share (Guess et al., 2019) more false political news on social media than any other age group. This is disturbing because older adults also vote at the highest rate (File, 2017). Similarly, misleading information about coronavirus is especially dangerous for older adults, who are at elevated risk of dying from COVID-19. Yet, without accurate data from social media companies, it is impossible to know exactly what false stories older adults see or why they are more likely to share them. For example, given that we lose peripheral acquaintances with age (Wrzus et al., 2013), older adults likely have close relationships with the people they friend and follow. With fewer weak ties, older adults may assume that content in their newsfeeds is accurate and quickly click ‘share’ (Brashier & Schacter, 2020), rather than pausing to think (Fazio, 2020). With access to users’ ages, the composition of their social networks, time spent viewing posts, and engagement with posts, we could better understand how older users experience social media. Given that repetition makes claims seem more credible to both young (Fazio et al., 2015) and older (Brashier et al., 2018) adults, it is also essential to know not just what people see, but also how often they see it. The data exist to test which social and cognitive factors leave older users particularly vulnerable to misinformation, but scientists need access.

Emotion, social media, and misinformation

Author: Brian E. Weeks Affiliation: Department of Communication and Media and Center for Political Studies, University of Michigan, USA

Misinformation thrives on social media because of emotion. False, emotional content is clicked on, diffuses widely and rapidly through social networks, and is often believed, particularly when it fits with one’s political worldview. Yet, the degree to which emotion influences exposure to, engagement with, and belief in misinformation on social media remains shrouded by insufficient data from prominent platforms. What is needed is a more comprehensive picture of the emotional nature of misinformation in social media environments. Open data from social media platforms would help address critical, unanswered questions like how often do people encounter emotionally evocative misinformation? How are individuals exposed to emotional content that is false (e.g., social sharing/incidental exposure, selective exposure, algorithmic filtering)? To what degree does misinformation play on emotions stemming from ideological, political, racial, or religious biases? How frequently do people engage (e.g., click, share, comment) with emotional misinformation and to what effect? Does encountering emotional falsehoods drive exposure to more extreme or partisan political content, contribute to polarization, and promote acceptance of false beliefs and conspiracy theories? Open data from social media platforms would also facilitate understanding of how different emotions like anger and fear uniquely amplify misinformation and deepen misperceptions. These questions demonstrate the urgent need to better understand the emotional environments in which misinformation flourishes on social media. More transparency and open data practices from social media platforms would illuminate the processes and mechanisms through which emotional misinformation is encountered, spread, and believed.

III. Richer datasets with improved validity

The case for studying obscure falsehoods.

Authors: Robert M. Bond (1), Lia C. Bozarth (2), Ceren Budak (2), R. Kelly Garrett (1), Jason J. Jones (3), Drew Margolin (4) Affiliations: (1) School of Communication, Ohio State University, USA, (2) School of Information, University of Michigan, USA, (3) Department of Sociology and Institute for Advanced Computational Science, Stony Brook University, USA, (4) Department of Communication, Cornell University, USA

Research on misinformation often focuses on non-representative sets of claims. Sometimes this decision is theoretically motivated, as when a falsehood is uniquely harmful (e.g., the thoroughly debunked “link” between vaccines and autism, see Motta et al., 2018). More often the decision reflects practical concerns, as when researchers use fact checkers’ archives to identify which claims to study (e.g., Vosoughi et al., 2018), despite the significant selection bias introduced by focusing on high-diffusion cases (Goel et al., 2012). Emphasizing “successful” misinformation also overlooks important variants, as most political falsehoods fail to find a large audience (Allen et al., 2020; Guess et al., 2019) and are shared primarily within small enclaves (Bail et al., 2019; Grinberg et al., 2019; Guess et al., 2020). Including both popular and unpopular misinformation in analyses would allow researchers to answer important questions. Do the two types of falsehoods differ in the extent to which they rely on viral or broadcast diffusion (i.e., their structural diffusion, see Goel et al., 2016)? Under what conditions will a falsehood go viral? Are there attributes that consistently characterize networks in which misinformation thrives? Are some types of events, policies, or technologies uniquely susceptible to mis- or disinformation campaigns? Answering these questions requires access to fine-grained temporal data about when content is shared, to aggregate characteristics about the populations that share them, and to characteristics about the networks in which the messages are shared. Importantly, though, it does not require access to individuals’ personal information or behavior.

WhatsApp data that could help research on misinformation

Authors: Fabrício Benevenuto (1), Pablo Ortellado (2) Affiliations: (1) Computer Science Department, Universidade Federal de Minas Gerais, Brazil, (2) Escola de Artes, Ciências e Humanidades, Universidade de São Paulo, Brazil

WhatsApp allegedly has been widely used to spread misinformation during elections, especially in Brazil and India (Tardaguila et al., 2018). Due to the private encrypted nature of the messages on WhatsApp, it is hard for researchers to track the dissemination of misinformation at scale and, ultimately, to investigate approaches able to mitigate the problem. Most of the research in this space has explored data shared in public groups (Resende et al., 2019). The research community would greatly benefit from WhatsApp disclosing the following information:

Aggregated information about users and uses of the platform. Number of users, number of groups, distribution of the size of those groups, distribution of frequency of messages sent to individual users and groups etc. This could be used for any researcher studying the platform and would allow anyone to better comprehend the use of the platform across countries.
Viral and widely-spread content. WhatsApp has been limiting the spread of content they consider to be viral. Viral content reaches a large number of users and may represent information that is of public interest. This content might be of interest not only for researchers studying misinformation, but also for journalism and fact checkers. While protecting privacy, WhatsApp could record the number of times a given content has been distributed and provide this information through an API. This information could be similar to that provided by Facebook through its Index API. This would allow researchers to measure the spread of a given content inside WhatsApp.
A random sample of names of groups. This would allow studies about how different groups use WhatsApp.

Misinformed citizens across social media platforms: Unraveling the effects of misinformation on social capital and civic participation

Authors: Jasmine McNealy (1), Seungahn Nah (2) Affiliations: (1) College of Journalism and Communication, University of Florida, USA, (2) School of Journalism and Communication, University of Oregon, USA

While research has long shown that informational use of news media has democratic value, there are few empirical findings on the civic consequences of exposure to misinformation across social media platforms. The proposed study develops a data infrastructure theory (DIT) grounded in communication infrastructure theory (CIT). CIT assumes that connections to community storytelling networks, such as local media, residents, and community organizations, foster civic engagement (Kim & Ball-Rokeach, 2006). In comparison, DIT posits that data available across social media will activate communication infrastructure, which, in turn may stimulate democratic values such as public discussion, social capital (e.g., social trust), and civic participation. We conceive social media platforms as data infrastructure for creating, conveying, and communicating misinformation embedded in a sheer volume of data. This study proposes several testable hypotheses: (a) exposure to misinformation across social media platforms will be negatively associated with trust in social media and social trust or trust in others, (b) exposure to misinformation across social media platforms will be negatively associated with less participation in public discussion, and (c) this exposure will lead to less involvement in civic and political activities. The hypotheses will be tested using a unique dataset that would include user consumption and production habits, as well as content exposure, and time spent on several social media platforms coupled with other information like an online survey and in-depth interviews of users who have been exposed to misinformation across social media platforms. In particular, we would examine the accuracy of the self-reported habits and engagement, as well as investigate social capital and civic participation in relation to the social media data set. Implications of misinformation exposure on democracy, and civic engagement will be discussed. We will also explore the impacts of misinformation on different communities in relation to both demographic data, as well as construct-developed categories of users.

IV. Disinformation campaigns

Data sharing protocols for content deletion and identity change activities to counter online manipulation.

Authors: Onur Varol (1), Kai-Cheng Yang (2), Emilio Ferrara (3), Alessandro Flammini (2), FiIippo Menczer (2) Affiliations: (1) Faculty of Engineering and Natural Sciences, Sabanci University, Turkey, (2) Observatory on Social Media, Indiana University, USA, (3) Information Sciences Institute, University of Southern California, USA

Efforts to disseminate disinformation and manipulate public opinion show similarities with early propaganda and persuasion campaigns (Lazer et al. 2018; Starbird, 2019; Varol & Uluturk, 2018). However, social media platforms now empower online information operations with improved means of concealing provenance, targeting vulnerable individuals, and rapid evaluation/optimization of strategies and narratives. All social media platforms offering programmatic interfaces (APIs) are vulnerable — and exploited. Inauthentic, coordinated, malicious accounts, whether human-controlled or automated (Ferrara et al., 2016; Shao et al., 2018; Varol et al., 2017; Yang et al., 2019), domestic or state-sponsored (Zannettou et al., 2019), or anywhere in between, have been weaponized to influence public conversations by amplifying and flooding content. Bot and troll accounts can systematically delete old posts and change identities to evade detection. Platforms should provide APIs for accredited researchers to access data needed to study, detect, and combat manipulation, such as statistics on deletions, profile changes, and 3rd-party application activities without breaching privacy preferences set by the users. Another severe limitation is the lack of access to historical data. Temporal anomalies leave marks of coordinated activities and remain detectable years after an operation (Varol & Uluturk, 2019). Access to past content deletions and changes of identities should be facilitated. Consistent data sharing protocols are needed to make temporal data about API activity, removed content, abuse reports, and suspended accounts available for research. The protocols should sanction research according to ethical principles and privacy regulations rather than inconsistent and ever-changing terms of service. Greater transparency is crucial to move research efforts from observational analyses to science- and data-driven policies (Aral & Eckles, 2019) to protect our marketplaces of ideas and our democracies.

What release of Russian 2016 troll data could reveal

Author: Kathleen Hall Jamieson Affiliation: Annenberg School of Communication, University of Pennsylvania, USA

Since the Trump presidency has reshaped the post-Cold War US-Russia-NATO relationship, history deserves an answer to the question: How likely is it that the 2016 Kremlin interventions made the presidential election close enough to be decided by 78,000 votes in three battleground states? In the second edition of Cyberwar: How Russian Hackers and Trolls Helped Elect a President , I argue that the changed media agenda created by press use of Russian-hacked Democratic content likely had a decisive effect on Democratic nominee Hillary Clinton’s standing in the polls and that the impact of the Russian trolls was negligible by comparison. Ironically, since much of the accessible Russian content is not directly election related, and the trolls used spam to artificially inflate their engagement and following metrics, it is likely that full transparency would further deflate estimates of the Russian social media saboteurs’ impact. To confirm that the platforms deserve to be let off the hook, they should do two things: (a) release all of the organic Russian content, as Twitter has done, to make it possible to determine how much was election-related and (b) reveal what they know about troll uptake in battleground states and across the nation by groups that the Kremlin-tied social media imposters were trying to demobilize (e.g., Black voters), mobilize (e.g., conservative Catholics and evangelical Protestants and those in military households), and shift (young Sanders’ supporters to Green party candidate Jill Stein).

V. Interventions

Evaluating interventions to fight misinformation.

Authors: Gordon Pennycook (1), David G. Rand (2) Affiliations: (1) Hill/Levene Schools of Business, University of Regina, Canada, (2) Sloan School of Management, Massachusetts Institute of Technology, USA

Our primary interest is in exploring the impact of interventions to reduce the spread of false and misleading content online. Experimental investigation of interventions, rather than implementation based on intuitive appeal, is essential for effectively meeting the misinformation challenge (Pennycook & Rand, 2020). Thus, our ideal experiments would involve randomly assigning users of platforms such as Facebook and Twitter to various intervention versus control conditions. We would then measure the interventions’ impact on which pieces of content (conditional on exposure) were shared, reacted to, and commented on, which links (e.g., to news sites) were clicked, and how long users spent reading each piece of content. Ideally, we would also pair these on-platform metrics with follow-up surveys in which we could directly assess users’ beliefs and attitudes. Specific interventions we would want to investigate include labeling news headlines with fact-checking warnings (Clayton et al., 2019; Pennycook, Bear, et al., 2020), prompts that nudge users to consider accuracy before sharing (Fazio, 2020; Pennycook, Epstein, et al., 2020; Pennycook, McPhetres et al., in press), and attempts to increase digital literacy (which likely also prime accuracy) (Guess et al., 2020). Finally, we would also be interested in assessing the impact of incorporating layperson (user) accuracy ratings, either of news sources (Epstein et al, 2020; Pennycook & Rand, 2019) or individual pieces of content (Allen, Arechar, et al. 2020), into social media ranking algorithms. Such investigations would provide clear, concrete evidence about which approaches are most effective (and which may actually be counterproductive). Without such evidence, it is impossible for the public to have faith in social media platforms’ efforts to curb misinformation.

The influence of fact checks and advertising

Authors: Michelle A. Amazeen (1), Chris Vargo (2) Affiliations: (1) Department of Mass Communication, Advertising and Public Relations, Boston University, USA, (2) Department of Advertising, Public Relations and Media Design, University of Colorado Boulder, USA

Social media platforms, including Facebook, have entered into agreements with third parties to provide fact-checks of content circulating on their platforms. Despite having partners around the world (Goldshlager, 2020), misinformation continues (Robertson, 2020). Fact-checking partners don’t know how well their efforts perform at reducing the spread of misinformation (Lu, 2019). Our dream research, consequently, centers around the transparency and accountability of social media efforts to address misinformation. We need an API endpoint that shows the specific actions platforms take once a message is identified as containing misinformation, including removal, warning labels, and downranking. When considering downranking or shadow banning, even more unknowns exist. Who still sees downranked content? How does that vary across demographics and psychographics? How do mitigation tactics affect the way audiences respond (liking, sharing, commenting, etc.)? Researchers need visibility into these actions to assess how political ideology, media use, and media literacy interact with the steps platforms are taking to correct misinformation. Furthermore, content on social media is narrowly targeted to specific audiences. Both political and commercial ads are targeted to users based on their pre-existing attitudes, beliefs, and fears (Borden King, 2020; Young & McGregor, 2020). While Facebook and Twitter have robust APIs, there is no way for researchers to identify ads in real-time. We also desire the ability to assess the damage targeted influence has on platforms and believe that researchers and platforms can work together to understand these consequences and ultimately build better systems.

Understanding digital mis- and disinformation: Origins, algorithms, and interventions

Authors: Alice E. Marwick (1), Deen Freelon (2), Daniel Kreiss (2), Shannon McGregor (2), Francesca Tripodi (3) Affiliations: (1) Department of Communication, University of North Carolina at Chapel Hill, USA, (2) Hussman School of Journalism, University of North Carolina at Chapel Hill, USA, (3) School of Information and Library Science, University of North Carolina at Chapel Hill, USA

1. Where and with whom does viral mis/disinformation originate? Determining the origin of a misleading story is currently next-to-impossible. With cross-platform data access, we could identify the first time a conspiratorial YouTube video or debunked political claim is shared on social media. Current research suggests that disinformation often comes from fringe networks and spreads through mainstream social media (Freelon et al., 2020), but we don’t know for sure, and we don’t know who creates and disseminates much of it. Determining where disinformation originates, and which platforms are most hospitable to its spread is the first step in decreasing its amplification and reach.

2. Which mis/disinformation correction strategies work best with which audiences or demographics? Current scholarship offers mixed findings and scant data on the effectiveness of oft-proposed solutions to mis/disinformation like fact-checking (e.g., Ecker et al., 2020; Lyons et al., 2020). With increased access and user consent, researchers could observe things such as organic fact-checking—how people react when a friend or group member points out incorrect information they have shared—and track whether corrections are equally effective across demographics, issues, and sources. This would allow us to create robust and effective intervention strategies with minimal unforeseen negative effects.

3. Which platform algorithms play the biggest role in spreading—or curbing—mis/disinformation? Critics claim that platform algorithms like Facebook’s news feed amplify harmful content, which we could test empirically. Does YouTube send people down a rabbit hole of radicalization? What role does Facebook’s Ad Auction play in driving mis/disinformation? Does TikTok use its algorithm to suppress or amplify demographics or viewpoints? This baseline knowledge is needed to assess, plan, and implement technical interventions, which are currently shrouded in obscurity. Providing scholars with the data to answer these questions is vital to understanding the cross- and multi-platform nature of—and solutions to—mis- and disinformation.

VI. Why data sharing is important

Dream research and the ownership of cultural artefacts: the need to reclaim the information ecology.

Authors: Stephan Lewandowsky (1,2), Ullrich K. H. Ecker (2), Ralph Hertwig (3), Philipp Lorenz-Spreen (3), Ronald E. Robertson (4) Affiliations: (1) School of Psychological Science, University of Bristol, UK, (2) School of Psychological Science, The University of Western Australia, Australia, (3) Max-Planck Institute for Human Development, Germany, (4) Network Science Institute, Northeastern University, USA

The information ecology produced by social media platforms and the data they collect is part of our cultural heritage. These data represent “libraries” of the present and the future, and they should be considered cultural artefacts that, like their physical counterparts, ought to be “owned” by the people who produced them—which is all of us. We must reclaim the information ecology for the people who created it. This is crucial for independent research in the public interest: to conduct such “dream research,” researchers must not be supplicants to social-media companies but should go straight to the users, recruiting people as “citizen scientists” and knowledge-co-creators. This can be achieved via dedicated research platforms and browser plug-ins, mobile applications, and other digital data collection tools that allow researchers access to people’s online activity subject to strict confidentiality and anonymity constraints. These data could constitute a common cultural good, permitting vital research without involvement or control by corporate interests. Some of the questions we could then address include examinations of (a) how malicious disinformation (e.g., concerning COVID-19) affects subsequent content engagement, and how this is shaped by countermeasures already in place or being designed by empirical research; (b) people’s motives to share information, in particular intentional sharing of information that is known to be false; (c) drivers of polarization and de-polarization; and (d) ways in which a common ground for evidence and rules of arguments can be re-established.

/ Platforms
/ Social Media

Cite this Essay

Pasquetto, I., Swire-Thompson, B., Amazeen, M. A., Benevenuto, F., Brashier, N. M., Bond, R. M., Bozarth, L. C., Budak, C., Ecker, U. K. H., Fazio, L. K., Ferrara, E., Flanagin, A. J., Flammini, A., Freelon, D., Grinberg, N., Hertwig, R., Jamieson, K. H., Joseph, K., Jones, J. J. . . .Yang, K. C. (2020). Tackling misinformation: What researchers could do with social media data. Harvard Kennedy School (HKS) Misinformation Review . https://doi.org/10.37016/mr-2020-49

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This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided that the original author and source are properly credited.

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How Trump’s Allies Are Winning the War Over Disinformation

Their claims of censorship have successfully stymied the effort to filter election lies online.

Three years after Mr. Trump spread falsehoods about his defeat online, social media platforms have fewer checks on the intentional spread of lies about elections. Credit... Emily Elconin for The New York Times

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By Jim Rutenberg and Steven Lee Myers

March 17, 2024

In the wake of the riot on Capitol Hill on Jan. 6, 2021, a groundswell built in Washington to rein in the onslaught of lies that had fueled the assault on the peaceful transfer of power.

Social media companies suspended Donald J. Trump, then the president, and many of his allies from the platforms they had used to spread misinformation about his defeat and whip up the attempt to overturn it. The Biden administration, Democrats in Congress and even some Republicans sought to do more to hold the companies accountable. Academic researchers wrestled with how to strengthen efforts to monitor false posts.

Mr. Trump and his allies embarked instead on a counteroffensive, a coordinated effort to block what they viewed as a dangerous effort to censor conservatives.

They have unquestionably prevailed.

Waged in the courts, in Congress and in the seething precincts of the internet, that effort has eviscerated attempts to shield elections from disinformation in the social media era. It tapped into — and then, critics say, twisted — the fierce debate over free speech and the government’s role in policing content.

Projects that were once bipartisan, including one started by the Trump administration, have been recast as deep-state conspiracies to rig elections. Facing legal and political blowback, the Biden administration has largely abandoned moves that might be construed as stifling political speech.

While little noticed by most Americans, the effort has helped cut a path for Mr. Trump’s attempt to recapture the presidency. Disinformation about elections is once again coursing through news feeds, aiding Mr. Trump as he fuels his comeback with falsehoods about the 2020 election.

“The censorship cartel must be dismantled and destroyed, and it must happen immediately,” he thundered at the start of his 2024 campaign.

The counteroffensive was led by former Trump aides and allies who had also pushed to overturn the 2020 election. They include Stephen Miller, the White House policy adviser; the attorneys general of Missouri and Louisiana, both Republicans; and lawmakers in Congress like Representative Jim Jordan, Republican of Ohio, who since last year has led a House subcommittee to investigate what it calls “the weaponization of government.”

Those involved draw financial support from conservative donors who have backed groups that promoted lies about voting in 2020. They have worked alongside an eclectic cast of characters, including Elon Musk, the billionaire who bought Twitter and vowed to make it a bastion of free speech, and Mike Benz, a former Trump administration official who previously produced content for a social media account that trafficked in posts about “white ethnic displacement.” (More recently, Mr. Benz originated the false assertion that Taylor Swift was a “psychological operation” asset for the Pentagon.)

Three years after Mr. Trump’s posts about rigged voting machines and stuffed ballot boxes went viral, he and his allies have achieved a stunning reversal of online fortune. Social media platforms now provide fewer checks against the intentional spread of lies about elections.

“The people that benefit from the spread of disinformation have effectively silenced many of the people that would try to call them out,” said Kate Starbird, a professor at the University of Washington whose research on disinformation made her a target of the effort.

It took aim at a patchwork of systems, started in Mr. Trump’s administration, that were intended to protect U.S. democracy from foreign interference. As those systems evolved to address domestic sources of misinformation, federal officials and private researchers began urging social media companies to do more to enforce their policies against harmful content.

That work has led to some of the most important First Amendment cases of the internet age, including one to be argued on Monday at the Supreme Court. That lawsuit, filed by the attorneys general of Missouri and Louisiana, accuses federal officials of colluding with or coercing the platforms to censor content critical of the government. The court’s decision, expected by June, could curtail the government’s latitude in monitoring content online.

The arguments strike at the heart of an unsettled question in modern American political life: In a world of unlimited online communications, in which anyone can reach huge numbers of people with unverified and false information, where is the line between protecting democracy and trampling on the right to free speech?

Even before the court rules, Mr. Trump’s allies have succeeded in paralyzing the Biden administration and the network of researchers who monitor disinformation.

Officials at the Department of Homeland Security and the State Department continue to monitor foreign disinformation, but the government has suspended virtually all cooperation with the social media platforms to address posts that originate in the United States.

“There’s just a chilling effect on all of this,” said Nina Jankowicz, a researcher who in 2022 briefly served as the executive director of a short-lived D.H.S. advisory board on disinformation. “Nobody wants to be caught up in it.”

Donald Trump holds a copy of the New York Post. The headline reads “The Ministry of Tweet.”

Fighting the ‘interpretive battle’

For Mr. Trump, banishment from social media was debilitating. His posts had been central to his political success, as was the army of adherents who cheered his messages and rallied behind his effort to hold onto office after he lost.

“WE have to use TIKTOK!!” read a memo prepared for Mr. Trump’s lead lawyer, Rudolph W. Giuliani, referring to a strategy to use social media to promote false messages about dead voters and vote-stealing software. “Content goes VIRAL here like no other platform!!!!! And there are MILLIONS of Trump supporters!”

After the violence on Jan. 6, Trump aides started working on how to “win the interpretive battle of the Trump history,” as one of them, Vincent Haley, had said in a previously unreported message found in the archives of the House investigation into the Jan. 6 attack. That would be crucial “for success in 2022 and 2024,” he added.

Once out of office, Mr. Trump built his own social platform, Truth Social, and his aides created a network of new organizations to advance the Trump agenda — and to prepare for his return.

Mr. Miller, Mr. Trump’s top policy adviser , created America First Legal, a nonprofit, to take on, as its mission statement put it, “an unholy alliance of corrupt special interests, big tech titans, fake news media and liberal Washington politicians.”

He solicited funding from conservative donors, drawing on a $27 million contribution from the Bradley Impact Fund , which had financed a web of groups that pushed “voter fraud” conspiracies in 2020. Another $1.3 million came from the Conservative Partnership Institute, considered the nonprofit nerve center of the Trump movement.

A key focus would be what he perceived as bias against conservatives on social media. “When you see people being banned off of Twitter and Facebook and other platforms,” he said in January 2021, “what you are seeing is the fundamental erosion of the concept of liberty and freedom in America.”

Mr. Biden’s administration was moving in the other direction. He came into office determined to take a tougher line against misinformation online — in large part because it was seen as an obstacle to bringing the coronavirus pandemic under control. D.H.S. officials were focused on bolstering defenses against election lies, which clearly had failed ahead of Jan. 6.

In one respect, that was clearer cut than matters of public health. There have long been special legal protections against providing false information about where, when and how to vote or intentionally sowing public confusion , or fear, to suppress voting.

Social media, with its pipeline to tens of millions of voters, presented powerful new pathways for antidemocratic tactics, but with far fewer of the regulatory and legal limits that exist for television, radio and newspapers.

The pitfalls were also clear: During the 2020 campaign, platforms had rushed to bury a New York Post article about Hunter Biden’s laptop out of concern that it might be tied to Russian interference. Conservatives saw it as an attempt to tilt the scales to Mr. Biden.

Administration officials said they were seeking a delicate balance between the First Amendment and social media’s rising power over public opinion.

“We’re in the business of critical infrastructure, and the most critical infrastructure is our cognitive infrastructure,” said Jen Easterly, the director of the Cybersecurity and Infrastructure Security Agency, whose responsibilities include protecting the national voting system. “Building that resilience to misinformation and disinformation, I think, is incredibly important.”

In early 2022, D.H.S. announced its first major answer to the conundrum: the Disinformation Governance Board. The board would serve as an advisory body and help coordinate anti-disinformation efforts across the department’s bureaucracy, officials said. Its director was Ms. Jankowicz, an expert in Russian disinformation.

The announcement ignited a political firestorm that killed the board only weeks after it began operating. Both liberals and conservatives raised questions about its reach and the potential for abuse.

The fury was most intense on the right. Mr. Miller, speaking on Fox News, slammed it as “something out of a dystopian sci-fi novel.”

Ms. Jankowicz said that such attacks were distorting but acknowledged that the announcement had struck a nerve.

“I think any American, when you hear, ‘Oh, the administration, the White House, is setting up something to censor Americans,’ even if that has no shred of evidence behind it, your ears are really going to prick up,” she said.

A legal assault

Among those who took note was Eric Schmitt, then the attorney general of Missouri.

He and other attorneys general had been a forceful part of Mr. Trump’s legal campaign to overturn his defeat. Now, they would lend legal firepower to block the fight against disinformation.

In May 2022, Mr. Schmitt and Jeff Landry, then the attorney general of Louisiana and now the governor, sued dozens of federal officials, including Dr. Anthony S. Fauci, the nation’s top expert on infectious diseases, who had become a villain to many conservatives.

The lawsuit picked up where others had failed. Mr. Trump and others had sued Facebook and Twitter, but those challenges stalled as courts effectively ruled that the companies had a right to ban content on their sites. The new case, known as Missouri v. Biden, argued that companies were not just barring users — they were being coerced into doing so by government officials.

The attorneys general filed the lawsuit in the Western District of Louisiana, where it fell to Judge Terry A. Doughty, a Trump appointee who had built a reputation for blocking Biden administration policies.

“A lot of these lawsuits against social media companies themselves were just dying in the graveyard in the Northern District of California,” Mr. Schmitt, who was elected to the U.S. Senate in 2022, said, referring to the liberal-leaning federal court in San Francisco. “And so our approach was a little bit different. We went directly at the government.”

The lawsuit was considered a long shot by experts, who noted that government officials were not issuing orders but urging the platforms to enforce their own policies. The decision to act was left to the companies, and more often than not, they did nothing.

Documents subpoenaed for the case showed extensive interactions between government officials and the platforms. In emails and text messages, people on both sides were alternately cooperative and confrontational. The platforms took seriously the administration’s complaints about content they said was misleading or false, but at the same time, they did not blindly carry out its bidding.

On Mr. Biden’s third day in office, a White House aide, Clarke Humphrey, wrote to Twitter flagging a post by Robert F. Kennedy Jr. falsely suggesting that the death of Hank Aaron, the baseball legend, had been caused by the Covid-19 vaccines. She asked an executive at the platform to begin the process of removing the post “as soon as possible.”

The post is still up.

Reframing the debate

In August 2022, a new organization, the Foundation for Freedom Online, posted a report on its website called “Department of Homeland Censorship: How D.H.S. Seized Power Over Online Speech.”

The group’s founder, a little-known former White House official named Mike Benz, claimed to have firsthand knowledge of how federal officials were “coordinating mass censorship of the internet.”

At the heart of Mr. Benz’s theory was the Election Integrity Partnership, a group created in the summer of 2020 to supplement government efforts to combat misinformation about the election that year.

The idea came from a group of college interns at the Cybersecurity and Infrastructure Security Agency, known as CISA. The students suggested that research institutions could help track and flag posts that might violate the platforms’ standards, feeding the information into a portal open to the agency, state and local governments and the platforms.

The project ultimately involved Stanford University, the University of Washington, the National Conference on Citizenship, the Atlantic Council’s Digital Forensic Research Lab and Graphika, a social media analytics firm. At its peak, it had 120 analysts, some of whom were college students.

It had what it considered successes, including spotting — and helping to stop — the spread of a false claim that a poll worker was burning Trump ballots in Erie, Pa. The approach could misfire, though. A separate, but related, CISA system flagged a tweet from a New York Times reporter accurately describing a printer problem at a voter center in Wisconsin, leading Twitter to affix an accuracy warning.

Decisions about whether to act remained with the platforms, which, in nearly two out of every three cases, did nothing.

In Mr. Benz’s telling, however, the government was using the partnership to get around the First Amendment, like outsourcing warfare to the private military contractor Blackwater.

Mr. Benz’s foundation for a time advertised itself as “a project of” Empower Oversight , a Republican group created by former Senate aides to support “whistle-blower” investigations.

Mr. Benz had previously lived a dual life. By day, he was a corporate lawyer in New York. In his off-hours, he toiled online under a social media avatar, Frame Game Radio, which railed against “the complete war on free speech” as it produced racist and antisemitic posts.

In videos and posts, Frame Game identified himself as a onetime member of the “Western chauvinist” group the Proud Boys, and as a Jew. Yet he blamed Jewish groups when he and others were suspended by social media companies. Warning about a looming demographic “white genocide,” Frame Game vented, “Anything pro white is called racist; anything white positive is racist.”

Mr. Benz did not respond to requests for comment. After NBC News first reported on Frame Game last fall, Mr. Benz called the account “a deradicalization project” to which he contributed in a “limited manner.” It was intended, he wrote on X, “by Jews to get people who hated Jews to stop hating Jews.”

Toward the end of 2018, Mr. Benz joined the Trump administration as a speechwriter for the housing and urban development secretary, Ben Carson. Mr. Benz’s posts were discovered by a colleague and brought to department management, according to a former official who insisted on anonymity to discuss a personnel matter.

As the election between Mr. Trump and Mr. Biden heated up, he joined Mr. Miller’s speech-writing team at the White House. He was there through the early days of the effort to keep Mr. Trump in power, and was involved in the search for statistical anomalies that could purport to show election fraud, according to testimony and records collected by House investigators, some of which were first uncovered by Kristen Ruby, a social media and public relations strategist.

In late November 2020, Mr. Benz was abruptly moved to the State Department as a deputy assistant secretary for international communications and information policy. It is unclear precisely what he did in the role. Mr. Benz has since claimed that the job, which he held for less than two months, gave him his expertise in cyberpolicy.

Mr. Benz’s report gained national attention when a conservative website, Just the News, wrote about it in September 2022. Four days later, Mr. Schmitt’s office sent requests for records to the University of Washington and others demanding information about their contacts with the government.

Mr. Schmitt soon amended his lawsuit to include nearly five pages detailing Mr. Benz’s work and asserting a new, broader claim: Not only was the government exerting pressure on the platforms, but it was also effectively deputizing the private researchers “to evade First Amendment and other legal restrictions.”

The scheme, Mr. Benz said, had “ambitious sights for 2022 and 2024.”

‘An aha moment’

In October 2022, Mr. Musk completed his purchase of Twitter and vowed to make the platform a forum for unfettered debate.

He quickly reversed the barring of Mr. Trump — calling it “morally wrong” — and loosened rules that had caused the suspensions of many of his followers.

He also set out to prove that Twitter’s previous management had too willingly cooperated with government officials. He released internal company communications to a select group of writers, among them Matt Taibbi and Michael Shellenberger.

The resulting project, which became known as the Twitter Files, began with an installment investigating Twitter’s decision to limit the reach of the Post article about Hunter Biden’s laptop.

The author of that dispatch, Mr. Taibbi, concluded that Twitter had limited the coverage amid general warnings from the F.B.I. that Russia could leak hacked materials to try to influence the 2020 election. Though he was critical of previous leadership at Twitter, he reported that he saw no evidence of direct government involvement.

In March 2023, Mr. Benz joined the fray. Both Mr. Taibbi and Mr. Benz participated in a live discussion on Twitter, which was co-hosted by Jennifer Lynn Lawrence, an organizer of the Trump rally that preceded the riot on Jan. 6.

As Mr. Taibbi described his work, Mr. Benz jumped in: “I believe I have all of the missing pieces of the puzzle.”

There was a far broader “scale of censorship the world has never experienced before,” he told Mr. Taibbi, who made plans to follow up.

Later, Mr. Shellenberger said that connecting with Mr. Benz had led to “a big aha moment.”

“The clouds parted, and the sunlight burst through the sky,” he said on a podcast. “It’s like, oh, my gosh, this guy is way, way farther down the rabbit hole than we even knew the rabbit hole went.”

A platform in Congress

A week after that online meeting, Mr. Taibbi and Mr. Shellenberger appeared on Capitol Hill as star witnesses for the Select Subcommittee on the Weaponization of the Federal Government. Mr. Benz sat behind them, listening as they detailed parts of his central thesis: This was not an imperfect attempt to balance free speech with democratic rights but a state-sponsored thought-policing system.

Mr. Shellenberger titled his written testimony, “The Censorship Industrial Complex.”

The committee had been created immediately after Republicans took control of the House in 2023 with a mandate to investigate, among other things, the actions taken by social media companies against conservatives.

It was led by Mr. Jordan, a lawmaker who helped spearhead the attempt to block certification of Mr. Biden’s victory and who has since worked closely with Mr. Miller and America First Legal.

“There are subpoenas that are going out on a daily, weekly basis,” Mr. Miller told Fox News in the first days of Republican control of the House, showing familiarity with the committee’s strategy.

Mr. Jordan’s committee soon sought documents from all those involved in the Election Integrity Partnership, as well as scores of government agencies and private researchers.

Mr. Miller followed with his own federal lawsuit on behalf of private plaintiffs in Missouri v. Biden, filing with D. John Sauer, the former solicitor general of Missouri who had led that case. (More recently, Mr. Sauer has represented Mr. Trump at the Supreme Court.)

Democrats in the House and legal experts questioned the collaboration as potentially unethical. Lawyers involved in the case have claimed that the subcommittee leaked selective parts of interviews conducted behind closed doors to America First Legal for use in its private lawsuits.

An amicus brief filed by the committee misrepresented facts and omitted evidence in ways that may have violated the Federal Rules of Civil Procedure, Representative Jerrold Nadler of New York wrote in a 46-page letter to Mr. Jordan.

A committee spokeswoman said the letter “deliberately misrepresents the evidence available to the committee to defend the Biden administration’s attacks on the First Amendment.”

The amicus brief, filed to the U.S. Court of Appeals for the Fifth Circuit, was drafted by a lawyer at Mr. Miller’s legal foundation.

Mr. Miller did not respond to requests for comment.

A chilling effect

By the summer of 2023, the legal and political effort was having an impact.

The organizations involved in the Election Integrity Partnership faced an avalanche of requests and, if they balked, subpoenas for any emails, text messages or other information involving the government or social media companies dating to 2015.

Complying consumed time and money. The threat of legal action dried up funding from donors — which had included philanthropies, corporations and the government — and struck fear in researchers worried about facing legal action and political threats online for the work.

“You had a lot of organizations doing this research,” a senior analyst at one of them said, speaking on the condition of anonymity because of fear of legal retribution. “Now, there are none.”

The Biden administration also found its hands tied. On July 4, 2023, Judge Doughty issued a sweeping injunction, saying that the government could not reach out to the platforms, or work with outside groups monitoring social media content, to address misinformation, except in a narrow set of circumstances.

The ruling went further than some of the plaintiffs in the Missouri case had expected. Judge Doughty even repeated an incorrect statistic first promoted by Mr. Benz: The partnership had flagged 22 million messages on Twitter alone, he wrote. In fact, it had flagged fewer than 5,000.

The Biden administration appealed.

While the judge said the administration could still take steps to stop foreign election interference or posts that mislead about voting requirements, it was unclear how it could without communicating “with social media companies on initiatives to prevent grave harm to the American people and our democratic processes,” the government asserted in its appeal.

In September, the U.S. Court of Appeals for the Fifth Circuit scaled the order back significantly, but still found the government had most likely overstepped the limits of the First Amendment. That sent the case to the Supreme Court, where justices recently expressed deep reservations about government intrusions in social media.

Ahead of the court’s decision, agencies across the government have virtually stopped communicating with social media companies, fearing the legal and political fallout as the presidential election approaches, according to several government officials who described the retreat on the condition of anonymity.

In a statement, Cait Conley, a senior adviser at the Cybersecurity and Infrastructure Security Agency, said the department was still strengthening partnerships to fight “risks posed by foreign actors.” She did not address online threats at home.

The platforms have also backed off. Facebook and YouTube announced that they would reverse their restrictions on content claiming that the 2020 election was stolen. The torrent of disinformation that the previous efforts had slowed, though not stopped, has resumed with even greater force.

Hailing the end of “that halcyon period of the censorship industry,” Mr. Benz has found new celebrity, sitting for interviews with Tucker Carlson and Russell Brand. His conspiracy theories, like the one about the Pentagon’s use of Taylor Swift, have aired on Fox News and become talking points for many Republicans.

The biggest winner, arguably, has been Mr. Trump, who casts himself as victim and avenger of a vast plot to muzzle his movement.

Mr. Biden is “building the most sophisticated censorship and information control apparatus in the world,” Mr. Trump said in a campaign email last week, “to crush free speech in America.”

Glenn Thrush and Luke Broadwater contributed reporting.

Jim Rutenberg is a writer at large for The Times and The New York Times Magazine and writes most often about media and politics. More about Jim Rutenberg

Steven Lee Myers covers misinformation for The Times. He has worked in Washington, Moscow, Baghdad and Beijing, where he contributed to the articles that won the Pulitzer Prize for public service in 2021. He is also the author of “The New Tsar: The Rise and Reign of Vladimir Putin.” More about Steven Lee Myers

Our Coverage of the 2024 Elections

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Biden’s re-election campaign had $71 million on hand at the end of February, more than double the money in Trump’s campaign account, as he continued to expand his fund-raising advantage over his rival.

Trump indicated that he was likely to back a 15-week federal ban on abortion , with exceptions for rape, incest and life-threatening emergencies.

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Ohio will almost certainly go for Trump this November. Senator Sherrod Brown, the last Democrat holding statewide office, will need to defy the gravity of the presidential contest to win a fourth term.

March 19 was the biggest primary night since Super Tuesday, and there were few surprises in the results. Here are the key takeaways .

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Front Psychiatry

Research trends in social media addiction and problematic social media use: A bibliometric analysis

Alfonso pellegrino.

1 Sasin School of Management, Chulalongkorn University, Bangkok, Thailand

Alessandro Stasi

2 Business Administration Division, Mahidol University International College, Mahidol University, Nakhon Pathom, Thailand

Veera Bhatiasevi

Associated data.

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

Despite their increasing ubiquity in people's lives and incredible advantages in instantly interacting with others, social media's impact on subjective well-being is a source of concern worldwide and calls for up-to-date investigations of the role social media plays in mental health. Much research has discovered how habitual social media use may lead to addiction and negatively affect adolescents' school performance, social behavior, and interpersonal relationships. The present study was conducted to review the extant literature in the domain of social media and analyze global research productivity during 2013–2022. Bibliometric analysis was conducted on 501 articles that were extracted from the Scopus database using the keywords social media addiction and problematic social media use. The data were then uploaded to VOSviewer software to analyze citations, co-citations, and keyword co-occurrences. Volume, growth trajectory, geographic distribution of the literature, influential authors, intellectual structure of the literature, and the most prolific publishing sources were analyzed. The bibliometric analysis presented in this paper shows that the US, the UK, and Turkey accounted for 47% of the publications in this field. Most of the studies used quantitative methods in analyzing data and therefore aimed at testing relationships between variables. In addition, the findings in this study show that most analysis were cross-sectional. Studies were performed on undergraduate students between the ages of 19–25 on the use of two social media platforms: Facebook and Instagram. Limitations as well as research directions for future studies are also discussed.

Introduction

Social media generally refers to third-party internet-based platforms that mainly focus on social interactions, community-based inputs, and content sharing among its community of users and only feature content created by their users and not that licensed from third parties ( 1 ). Social networking sites such as Facebook, Instagram, and TikTok are prominent examples of social media that allow people to stay connected in an online world regardless of geographical distance or other obstacles ( 2 , 3 ). Recent evidence suggests that social networking sites have become increasingly popular among adolescents following the strict policies implemented by many countries to counter the COVID-19 pandemic, including social distancing, “lockdowns,” and quarantine measures ( 4 ). In this new context, social media have become an essential part of everyday life, especially for children and adolescents ( 5 ). For them such media are a means of socialization that connect people together. Interestingly, social media are not only used for social communication and entertainment purposes but also for sharing opinions, learning new things, building business networks, and initiate collaborative projects ( 6 ).

Among the 7.91 billion people in the world as of 2022, 4.62 billion active social media users, and the average time individuals spent using the internet was 6 h 58 min per day with an average use of social media platforms of 2 h and 27 min ( 7 ). Despite their increasing ubiquity in people's lives and the incredible advantages they offer to instantly interact with people, an increasing number of studies have linked social media use to negative mental health consequences, such as suicidality, loneliness, and anxiety ( 8 ). Numerous sources have expressed widespread concern about the effects of social media on mental health. A 2011 report by the American Academy of Pediatrics (AAP) identifies a phenomenon known as Facebook depression which may be triggered “when preteens and teens spend a great deal of time on social media sites, such as Facebook, and then begin to exhibit classic symptoms of depression” ( 9 ). Similarly, the UK's Royal Society for Public Health (RSPH) claims that there is a clear evidence of the relationship between social media use and mental health issues based on a survey of nearly 1,500 people between the ages of 14–24 ( 10 ). According to some authors, the increase in usage frequency of social media significantly increases the risks of clinical disorders described (and diagnosed) as “Facebook depression,” “fear of missing out” (FOMO), and “social comparison orientation” (SCO) ( 11 ). Other risks include sexting ( 12 ), social media stalking ( 13 ), cyber-bullying ( 14 ), privacy breaches ( 15 ), and improper use of technology. Therefore, social media's impact on subjective well-being is a source of concern worldwide and calls for up-to-date investigations of the role social media plays with regard to mental health ( 8 ). Many studies have found that habitual social media use may lead to addiction and thus negatively affect adolescents' school performance, social behavior, and interpersonal relationships ( 16 – 18 ). As a result of addiction, the user becomes highly engaged with online activities motivated by an uncontrollable desire to browse through social media pages and “devoting so much time and effort to it that it impairs other important life areas” ( 19 ).

Given these considerations, the present study was conducted to review the extant literature in the domain of social media and analyze global research productivity during 2013–2022. The study presents a bibliometric overview of the leading trends with particular regard to “social media addiction” and “problematic social media use.” This is valuable as it allows for a comprehensive overview of the current state of this field of research, as well as identifies any patterns or trends that may be present. Additionally, it provides information on the geographical distribution and prolific authors in this area, which may help to inform future research endeavors.

In terms of bibliometric analysis of social media addiction research, few studies have attempted to review the existing literature in the domain extensively. Most previous bibliometric studies on social media addiction and problematic use have focused mainly on one type of screen time activity such as digital gaming or texting ( 20 ) and have been conducted with a focus on a single platform such as Facebook, Instagram, or Snapchat ( 21 , 22 ). The present study adopts a more comprehensive approach by including all social media platforms and all types of screen time activities in its analysis.

Additionally, this review aims to highlight the major themes around which the research has evolved to date and draws some guidance for future research directions. In order to meet these objectives, this work is oriented toward answering the following research questions:

(1) What is the current status of research focusing on social media addiction?
(2) What are the key thematic areas in social media addiction and problematic use research?
(3) What is the intellectual structure of social media addiction as represented in the academic literature?
(4) What are the key findings of social media addiction and problematic social media research?
(5) What possible future research gaps can be identified in the field of social media addiction?

These research questions will be answered using bibliometric analysis of the literature on social media addiction and problematic use. This will allow for an overview of the research that has been conducted in this area, including information on the most influential authors, journals, countries of publication, and subject areas of study. Part 2 of the study will provide an examination of the intellectual structure of the extant literature in social media addiction while Part 3 will discuss the research methodology of the paper. Part 4 will discuss the findings of the study followed by a discussion under Part 5 of the paper. Finally, in Part 7, gaps in current knowledge about this field of research will be identified.

Literature review

Social media addiction research context.

Previous studies on behavioral addictions have looked at a lot of different factors that affect social media addiction focusing on personality traits. Although there is some inconsistency in the literature, numerous studies have focused on three main personality traits that may be associated with social media addiction, namely anxiety, depression, and extraversion ( 23 , 24 ).

It has been found that extraversion scores are strongly associated with increased use of social media and addiction to it ( 25 , 26 ). People with social anxiety as well as people who have psychiatric disorders often find online interactions extremely appealing ( 27 ). The available literature also reveals that the use of social media is positively associated with being female, single, and having attention deficit hyperactivity disorder (ADHD), obsessive compulsive disorder (OCD), or anxiety ( 28 ).

In a study by Seidman ( 29 ), the Big Five personality traits were assessed using Saucier's ( 30 ) Mini-Markers Scale. Results indicated that neurotic individuals use social media as a safe place for expressing their personality and meet belongingness needs. People affected by neurosis tend to use online social media to stay in touch with other people and feel better about their social lives ( 31 ). Narcissism is another factor that has been examined extensively when it comes to social media, and it has been found that people who are narcissistic are more likely to become addicted to social media ( 32 ). In this case users want to be seen and get “likes” from lots of other users. Longstreet and Brooks ( 33 ) did a study on how life satisfaction depends on how much money people make. Life satisfaction was found to be negatively linked to social media addiction, according to the results. When social media addiction decreases, the level of life satisfaction rises. But results show that in lieu of true-life satisfaction people use social media as a substitute (for temporary pleasure vs. longer term happiness).

Researchers have discovered similar patterns in students who tend to rank high in shyness: they find it easier to express themselves online rather than in person ( 34 , 35 ). With the use of social media, shy individuals have the opportunity to foster better quality relationships since many of their anxiety-related concerns (e.g., social avoidance and fear of social devaluation) are significantly reduced ( 36 , 37 ).

Problematic use of social media

The amount of research on problematic use of social media has dramatically increased since the last decade. But using social media in an unhealthy manner may not be considered an addiction or a disorder as this behavior has not yet been formally categorized as such ( 38 ). Although research has shown that people who use social media in a negative way often report negative health-related conditions, most of the data that have led to such results and conclusions comprise self-reported data ( 39 ). The dimensions of excessive social media usage are not exactly known because there are not enough diagnostic criteria and not enough high-quality long-term studies available yet. This is what Zendle and Bowden-Jones ( 40 ) noted in their own research. And this is why terms like “problematic social media use” have been used to describe people who use social media in a negative way. Furthermore, if a lot of time is spent on social media, it can be hard to figure out just when it is being used in a harmful way. For instance, people easily compare their appearance to what they see on social media, and this might lead to low self-esteem if they feel they do not look as good as the people they are following. According to research in this domain, the extent to which an individual engages in photo-related activities (e.g., taking selfies, editing photos, checking other people's photos) on social media is associated with negative body image concerns. Through curated online images of peers, adolescents face challenges to their self-esteem and sense of self-worth and are increasingly isolated from face-to-face interaction.

To address this problem the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) has been used by some scholars ( 41 , 42 ). These scholars have used criteria from the DSM-V to describe one problematic social media use, internet gaming disorder, but such criteria could also be used to describe other types of social media disorders. Franchina et al. ( 43 ) and Scott and Woods ( 44 ), for example, focus their attention on individual-level factors (like fear of missing out) and family-level factors (like childhood abuse) that have been used to explain why people use social media in a harmful way. Friends-level factors have also been explored as a social well-being measurement to explain why people use social media in a malevolent way and demonstrated significant positive correlations with lower levels of friend support ( 45 ). Macro-level factors have also been suggested, such as the normalization of surveillance ( 46 ) and the ability to see what people are doing online ( 47 ). Gender and age seem to be highly associated to the ways people use social media negatively. Particularly among girls, social media use is consistently associated with mental health issues ( 41 , 48 , 49 ), an association more common among older girls than younger girls ( 46 , 48 ).

Most studies have looked at the connection between social media use and its effects (such as social media addiction) and a number of different psychosomatic disorders. In a recent study conducted by Vannucci and Ohannessian ( 50 ), the use of social media appears to have a variety of effects “on psychosocial adjustment during early adolescence, with high social media use being the most problematic.” It has been found that people who use social media in a harmful way are more likely to be depressed, anxious, have low self-esteem, be more socially isolated, have poorer sleep quality, and have more body image dissatisfaction. Furthermore, harmful social media use has been associated with unhealthy lifestyle patterns (for example, not getting enough exercise or having trouble managing daily obligations) as well as life threatening behaviors such as illicit drug use, excessive alcohol consumption and unsafe sexual practices ( 51 , 52 ).

A growing body of research investigating social media use has revealed that the extensive use of social media platforms is correlated with a reduced performance on cognitive tasks and in mental effort ( 53 ). Overall, it appears that individuals who have a problematic relationship with social media or those who use social media more frequently are more likely to develop negative health conditions.

Social media addiction and problematic use systematic reviews

Previous studies have revealed the detrimental impacts of social media addiction on users' health. A systematic review by Khan and Khan ( 20 ) has pointed out that social media addiction has a negative impact on users' mental health. For example, social media addiction can lead to stress levels rise, loneliness, and sadness ( 54 ). Anxiety is another common mental health problem associated with social media addiction. Studies have found that young adolescents who are addicted to social media are more likely to suffer from anxiety than people who are not addicted to social media ( 55 ). In addition, social media addiction can also lead to physical health problems, such as obesity and carpal tunnel syndrome a result of spending too much time on the computer ( 22 ).

Apart from the negative impacts of social media addiction on users' mental and physical health, social media addiction can also lead to other problems. For example, social media addiction can lead to financial problems. A study by Sharif and Yeoh ( 56 ) has found that people who are addicted to social media tend to spend more money than those who are not addicted to social media. In addition, social media addiction can also lead to a decline in academic performance. Students who are addicted to social media are more likely to have lower grades than those who are not addicted to social media ( 57 ).

Research methodology

Bibliometric analysis.

Merigo et al. ( 58 ) use bibliometric analysis to examine, organize, and analyze a large body of literature from a quantitative, objective perspective in order to assess patterns of research and emerging trends in a certain field. A bibliometric methodology is used to identify the current state of the academic literature, advance research. and find objective information ( 59 ). This technique allows the researchers to examine previous scientific work, comprehend advancements in prior knowledge, and identify future study opportunities.

To achieve this objective and identify the research trends in social media addiction and problematic social media use, this study employs two bibliometric methodologies: performance analysis and science mapping. Performance analysis uses a series of bibliometric indicators (e.g., number of annual publications, document type, source type, journal impact factor, languages, subject area, h-index, and countries) and aims at evaluating groups of scientific actors on a particular topic of research. VOSviewer software ( 60 ) was used to carry out the science mapping. The software is used to visualize a particular body of literature and map the bibliographic material using the co-occurrence analysis of author, index keywords, nations, and fields of publication ( 61 , 62 ).

Data collection

After picking keywords, designing the search strings, and building up a database, the authors conducted a bibliometric literature search. Scopus was utilized to gather exploration data since it is a widely used database that contains the most comprehensive view of the world's research output and provides one of the most effective search engines. If the research was to be performed using other database such as Web Of Science or Google Scholar the authors may have obtained larger number of articles however they may not have been all particularly relevant as Scopus is known to have the most widest and most relevant scholar search engine in marketing and social science. A keyword search for “social media addiction” OR “problematic social media use” yielded 553 papers, which were downloaded from Scopus. The information was gathered in March 2022, and because the Scopus database is updated on a regular basis, the results may change in the future. Next, the authors examined the titles and abstracts to see whether they were relevant to the topics treated. There were two common grounds for document exclusion. First, while several documents emphasized the negative effects of addiction in relation to the internet and digital media, they did not focus on social networking sites specifically. Similarly, addiction and problematic consumption habits were discussed in relation to social media in several studies, although only in broad terms. This left a total of 511 documents. Articles were then limited only to journal articles, conference papers, reviews, books, and only those published in English. This process excluded 10 additional documents. Then, the relevance of the remaining articles was finally checked by reading the titles, abstracts, and keywords. Documents were excluded if social networking sites were only mentioned as a background topic or very generally. This resulted in a final selection of 501 research papers, which were then subjected to bibliometric analysis (see Figure 1 ).

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Preferred reporting items for systematic reviews and meta-analysis (PRISMA) flowchart showing the search procedures used in the review.

After identifying 501 Scopus files, bibliographic data related to these documents were imported into an Excel sheet where the authors' names, their affiliations, document titles, keywords, abstracts, and citation figures were analyzed. These were subsequently uploaded into VOSViewer software version 1.6.8 to begin the bibliometric review. Descriptive statistics were created to define the whole body of knowledge about social media addiction and problematic social media use. VOSViewer was used to analyze citation, co-citation, and keyword co-occurrences. According to Zupic and Cater ( 63 ), co-citation analysis measures the influence of documents, authors, and journals heavily cited and thus considered influential. Co-citation analysis has the objective of building similarities between authors, journals, and documents and is generally defined as the frequency with which two units are cited together within the reference list of a third article.

The implementation of social media addiction performance analysis was conducted according to the models recently introduced by Karjalainen et al. ( 64 ) and Pattnaik ( 65 ). Throughout the manuscript there are operational definitions of relevant terms and indicators following a standardized bibliometric approach. The cumulative academic impact (CAI) of the documents was measured by the number of times they have been cited in other scholarly works while the fine-grained academic impact (FIA) was computed according to the authors citation analysis and authors co-citation analysis within the reference lists of documents that have been specifically focused on social media addiction and problematic social media use.

Results of the study presented here include the findings on social media addiction and social media problematic use. The results are presented by the foci outlined in the study questions.

Volume, growth trajectory, and geographic distribution of the literature

After performing the Scopus-based investigation of the current literature regarding social media addiction and problematic use of social media, the authors obtained a knowledge base consisting of 501 documents comprising 455 journal articles, 27 conference papers, 15 articles reviews, 3 books and 1 conference review. The included literature was very recent. As shown in Figure 2 , publication rates started very slowly in 2013 but really took off in 2018, after which publications dramatically increased each year until a peak was reached in 2021 with 195 publications. Analyzing the literature published during the past decade reveals an exponential increase in scholarly production on social addiction and its problematic use. This might be due to the increasingly widespread introduction of social media sites in everyday life and the ubiquitous diffusion of mobile devices that have fundamentally impacted human behavior. The dip in the number of publications in 2022 is explained by the fact that by the time the review was carried out the year was not finished yet and therefore there are many articles still in press.

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Annual volume of social media addiction or social media problematic use ( n = 501).

The geographical distribution trends of scholarly publications on social media addiction or problematic use of social media are highlighted in Figure 3 . The articles were assigned to a certain country according to the nationality of the university with whom the first author was affiliated with. The figure shows that the most productive countries are the USA (92), the U.K. (79), and Turkey ( 63 ), which combined produced 236 articles, equal to 47% of the entire scholarly production examined in this bibliometric analysis. Turkey has slowly evolved in various ways with the growth of the internet and social media. Anglo-American scholarly publications on problematic social media consumer behavior represent the largest research output. Yet it is interesting to observe that social networking sites studies are attracting many researchers in Asian countries, particularly China. For many Chinese people, social networking sites are a valuable opportunity to involve people in political activism in addition to simply making purchases ( 66 ).

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Global dispersion of social networking sites in relation to social media addiction or social media problematic use.

Analysis of influential authors

This section analyses the high-impact authors in the Scopus-indexed knowledge base on social networking sites in relation to social media addiction or problematic use of social media. It provides valuable insights for establishing patterns of knowledge generation and dissemination of literature about social networking sites relating to addiction and problematic use.

Table 1 acknowledges the top 10 most highly cited authors with the highest total citations in the database.

Highly cited authors on social media addiction and problematic use ( n = 501).

a Total link strength indicates the number of publications in which an author occurs.

Table 1 shows that MD Griffiths (sixty-five articles), CY Lin (twenty articles), and AH Pakpour (eighteen articles) are the most productive scholars according to the number of Scopus documents examined in the area of social media addiction and its problematic use . If the criteria are changed and authors ranked according to the overall number of citations received in order to determine high-impact authors, the same three authors turn out to be the most highly cited authors. It should be noted that these highly cited authors tend to enlist several disciplines in examining social media addiction and problematic use. Griffiths, for example, focuses on behavioral addiction stemming from not only digital media usage but also from gambling and video games. Lin, on the other hand, focuses on the negative effects that the internet and digital media can have on users' mental health, and Pakpour approaches the issue from a behavioral medicine perspective.

Intellectual structure of the literature

In this part of the paper, the authors illustrate the “intellectual structure” of the social media addiction and the problematic use of social media's literature. An author co-citation analysis (ACA) was performed which is displayed as a figure that depicts the relations between highly co-cited authors. The study of co-citation assumes that strongly co-cited authors carry some form of intellectual similarity ( 67 ). Figure 4 shows the author co-citation map. Nodes represent units of analysis (in this case scholars) and network ties represent similarity connections. Nodes are sized according to the number of co-citations received—the bigger the node, the more co-citations it has. Adjacent nodes are considered intellectually similar.

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Two clusters, representing the intellectual structure of the social media and its problematic use literature.

Scholars belonging to the green cluster (Mental Health and Digital Media Addiction) have extensively published on medical analysis tools and how these can be used to heal users suffering from addiction to digital media, which can range from gambling, to internet, to videogame addictions. Scholars in this school of thought focus on the negative effects on users' mental health, such as depression, anxiety, and personality disturbances. Such studies focus also on the role of screen use in the development of mental health problems and the increasing use of medical treatments to address addiction to digital media. They argue that addiction to digital media should be considered a mental health disorder and treatment options should be made available to users.

In contrast, scholars within the red cluster (Social Media Effects on Well Being and Cyberpsychology) have focused their attention on the effects of social media toward users' well-being and how social media change users' behavior, focusing particular attention on the human-machine interaction and how methods and models can help protect users' well-being. Two hundred and two authors belong to this group, the top co-cited being Andreassen (667 co-citations), Pallasen (555 co-citations), and Valkenburg (215 co-citations). These authors have extensively studied the development of addiction to social media, problem gambling, and internet addiction. They have also focused on the measurement of addiction to social media, cyberbullying, and the dark side of social media.

Most influential source title in the field of social media addiction and its problematic use

To find the preferred periodicals in the field of social media addiction and its problematic use, the authors have selected 501 articles published in 263 journals. Table 2 gives a ranked list of the top 10 journals that constitute the core publishing sources in the field of social media addiction research. In doing so, the authors analyzed the journal's impact factor, Scopus Cite Score, h-index, quartile ranking, and number of publications per year.

Top 10 most cited and more frequently mentioned documents in the field of social media addiction.

The journal Addictive Behaviors topped the list, with 700 citations and 22 publications (4.3%), followed by Computers in Human Behaviors , with 577 citations and 13 publications (2.5%), Journal of Behavioral Addictions , with 562 citations and 17 publications (3.3%), and International Journal of Mental Health and Addiction , with 502 citations and 26 publications (5.1%). Five of the 10 most productive journals in the field of social media addiction research are published by Elsevier (all Q1 rankings) while Springer and Frontiers Media published one journal each.

Documents citation analysis identified the most influential and most frequently mentioned documents in a certain scientific field. Andreassen has received the most citations among the 10 most significant papers on social media addiction, with 405 ( Table 2 ). The main objective of this type of studies was to identify the associations and the roles of different variables as predictors of social media addiction (e.g., ( 19 , 68 , 69 )). According to general addiction models, the excessive and problematic use of digital technologies is described as “being overly concerned about social media, driven by an uncontrollable motivation to log on to or use social media, and devoting so much time and effort to social media that it impairs other important life areas” ( 27 , 70 ). Furthermore, the purpose of several highly cited studies ( 31 , 71 ) was to analyse the connections between young adults' sleep quality and psychological discomfort, depression, self-esteem, and life satisfaction and the severity of internet and problematic social media use, since the health of younger generations and teenagers is of great interest this may help explain the popularity of such papers. Despite being the most recent publication Lin et al.'s work garnered more citations annually. The desire to quantify social media addiction in individuals can also help explain the popularity of studies which try to develop measurement scales ( 42 , 72 ). Some of the highest-ranked publications are devoted to either the presentation of case studies or testing relationships among psychological constructs ( 73 ).

Keyword co-occurrence analysis

The research question, “What are the key thematic areas in social media addiction literature?” was answered using keyword co-occurrence analysis. Keyword co-occurrence analysis is conducted to identify research themes and discover keywords. It mainly examines the relationships between co-occurrence keywords in a wide variety of literature ( 74 ). In this approach, the idea is to explore the frequency of specific keywords being mentioned together.

Utilizing VOSviewer, the authors conducted a keyword co-occurrence analysis to characterize and review the developing trends in the field of social media addiction. The top 10 most frequent keywords are presented in Table 3 . The results indicate that “social media addiction” is the most frequent keyword (178 occurrences), followed by “problematic social media use” (74 occurrences), “internet addiction” (51 occurrences), and “depression” (46 occurrences). As shown in the co-occurrence network ( Figure 5 ), the keywords can be grouped into two major clusters. “Problematic social media use” can be identified as the core theme of the green cluster. In the red cluster, keywords mainly identify a specific aspect of problematic social media use: social media addiction.

Frequency of occurrence of top 10 keywords.

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Keywords co-occurrence map. Threshold: 5 co-occurrences.

The results of the keyword co-occurrence analysis for journal articles provide valuable perspectives and tools for understanding concepts discussed in past studies of social media usage ( 75 ). More precisely, it can be noted that there has been a large body of research on social media addiction together with other types of technological addictions, such as compulsive web surfing, internet gaming disorder, video game addiction and compulsive online shopping ( 76 – 78 ). This field of research has mainly been directed toward teenagers, middle school students, and college students and university students in order to understand the relationship between social media addiction and mental health issues such as depression, disruptions in self-perceptions, impairment of social and emotional activity, anxiety, neuroticism, and stress ( 79 – 81 ).

The findings presented in this paper show that there has been an exponential increase in scholarly publications—from two publications in 2013 to 195 publications in 2021. There were 45 publications in 2022 at the time this study was conducted. It was interesting to observe that the US, the UK, and Turkey accounted for 47% of the publications in this field even though none of these countries are in the top 15 countries in terms of active social media penetration ( 82 ) although the US has the third highest number of social media users ( 83 ). Even though China and India have the highest number of social media users ( 83 ), first and second respectively, they rank fifth and tenth in terms of publications on social media addiction or problematic use of social media. In fact, the US has almost double the number of publications in this field compared to China and almost five times compared to India. Even though East Asia, Southeast Asia, and South Asia make up the top three regions in terms of worldwide social media users ( 84 ), except for China and India there have been only a limited number of publications on social media addiction or problematic use. An explanation for that could be that there is still a lack of awareness on the negative consequences of the use of social media and the impact it has on the mental well-being of users. More research in these regions should perhaps be conducted in order to understand the problematic use and addiction of social media so preventive measures can be undertaken.

From the bibliometric analysis, it was found that most of the studies examined used quantitative methods in analyzing data and therefore aimed at testing relationships between variables. In addition, many studies were empirical, aimed at testing relationships based on direct or indirect observations of social media use. Very few studies used theories and for the most part if they did they used the technology acceptance model and social comparison theories. The findings presented in this paper show that none of the studies attempted to create or test new theories in this field, perhaps due to the lack of maturity of the literature. Moreover, neither have very many qualitative studies been conducted in this field. More qualitative research in this field should perhaps be conducted as it could explore the motivations and rationales from which certain users' behavior may arise.

The authors found that almost all the publications on social media addiction or problematic use relied on samples of undergraduate students between the ages of 19–25. The average daily time spent by users worldwide on social media applications was highest for users between the ages of 40–44, at 59.85 min per day, followed by those between the ages of 35–39, at 59.28 min per day, and those between the ages of 45–49, at 59.23 per day ( 85 ). Therefore, more studies should be conducted exploring different age groups, as users between the ages of 19–25 do not represent the entire population of social media users. Conducting studies on different age groups may yield interesting and valuable insights to the field of social media addiction. For example, it would be interesting to measure the impacts of social media use among older users aged 50 years or older who spend almost the same amount of time on social media as other groups of users (56.43 min per day) ( 85 ).

A majority of the studies tested social media addiction or problematic use based on only two social media platforms: Facebook and Instagram. Although Facebook and Instagram are ranked first and fourth in terms of most popular social networks by number of monthly users, it would be interesting to study other platforms such as YouTube, which is ranked second, and WhatsApp, which is ranked third ( 86 ). Furthermore, TikTok would also be an interesting platform to study as it has grown in popularity in recent years, evident from it being the most downloaded application in 2021, with 656 million downloads ( 87 ), and is ranked second in Q1 of 2022 ( 88 ). Moreover, most of the studies focused only on one social media platform. Comparing different social media platforms would yield interesting results because each platform is different in terms of features, algorithms, as well as recommendation engines. The purpose as well as the user behavior for using each platform is also different, therefore why users are addicted to these platforms could provide a meaningful insight into social media addiction and problematic social media use.

Lastly, most studies were cross-sectional, and not longitudinal, aiming at describing results over a certain point in time and not over a long period of time. A longitudinal study could better describe the long-term effects of social media use.

This study was conducted to review the extant literature in the field of social media and analyze the global research productivity during the period ranging from 2013 to 2022. The study presents a bibliometric overview of the leading trends with particular regard to “social media addiction” and “problematic social media use.” The authors applied science mapping to lay out a knowledge base on social media addiction and its problematic use. This represents the first large-scale analysis in this area of study.

A keyword search of “social media addiction” OR “problematic social media use” yielded 553 papers, which were downloaded from Scopus. After performing the Scopus-based investigation of the current literature regarding social media addiction and problematic use, the authors ended up with a knowledge base consisting of 501 documents comprising 455 journal articles, 27 conference papers, 15 articles reviews, 3 books, and 1 conference review.

The geographical distribution trends of scholarly publications on social media addiction or problematic use indicate that the most productive countries were the USA (92), the U.K. (79), and Turkey ( 63 ), which together produced 236 articles. Griffiths (sixty-five articles), Lin (twenty articles), and Pakpour (eighteen articles) were the most productive scholars according to the number of Scopus documents examined in the area of social media addiction and its problematic use. An author co-citation analysis (ACA) was conducted which generated a layout of social media effects on well-being and cyber psychology as well as mental health and digital media addiction in the form of two research literature clusters representing the intellectual structure of social media and its problematic use.

The preferred periodicals in the field of social media addiction and its problematic use were Addictive Behaviors , with 700 citations and 22 publications, followed by Computers in Human Behavior , with 577 citations and 13 publications, and Journal of Behavioral Addictions , with 562 citations and 17 publications. Keyword co-occurrence analysis was used to investigate the key thematic areas in the social media literature, as represented by the top three keyword phrases in terms of their frequency of occurrence, namely, “social media addiction,” “problematic social media use,” and “social media addiction.”

This research has a few limitations. The authors used science mapping to improve the comprehension of the literature base in this review. First and foremost, the authors want to emphasize that science mapping should not be utilized in place of established review procedures, but rather as a supplement. As a result, this review can be considered the initial stage, followed by substantive research syntheses that examine findings from recent research. Another constraint stems from how 'social media addiction' is defined. The authors overcame this limitation by inserting the phrase “social media addiction” OR “problematic social media use” in the search string. The exclusive focus on SCOPUS-indexed papers creates a third constraint. The SCOPUS database has a larger number of papers than does Web of Science although it does not contain all the publications in a given field.

Although the total body of literature on social media addiction is larger than what is covered in this review, the use of co-citation analyses helped to mitigate this limitation. This form of bibliometric study looks at all the publications listed in the reference list of the extracted SCOPUS database documents. As a result, a far larger dataset than the one extracted from SCOPUS initially has been analyzed.

The interpretation of co-citation maps should be mentioned as a last constraint. The reason is that the procedure is not always clear, so scholars must have a thorough comprehension of the knowledge base in order to make sense of the result of the analysis ( 63 ). This issue was addressed by the authors' expertise, but it remains somewhat subjective.

Implications

The findings of this study have implications mainly for government entities and parents. The need for regulation of social media addiction is evident when considering the various risks associated with habitual social media use. Social media addiction may lead to negative consequences for adolescents' school performance, social behavior, and interpersonal relationships. In addition, social media addiction may also lead to other risks such as sexting, social media stalking, cyber-bullying, privacy breaches, and improper use of technology. Given the seriousness of these risks, it is important to have regulations in place to protect adolescents from the harms of social media addiction.

Regulation of social media platforms

One way that regulation could help protect adolescents from the harms of social media addiction is by limiting their access to certain websites or platforms. For example, governments could restrict adolescents' access to certain websites or platforms during specific hours of the day. This would help ensure that they are not spending too much time on social media and are instead focusing on their schoolwork or other important activities.

Another way that regulation could help protect adolescents from the harms of social media addiction is by requiring companies to put warning labels on their websites or apps. These labels would warn adolescents about the potential risks associated with excessive use of social media.

Finally, regulation could also require companies to provide information about how much time each day is recommended for using their website or app. This would help adolescents make informed decisions about how much time they want to spend on social media each day. These proposed regulations would help to protect children from the dangers of social media, while also ensuring that social media companies are more transparent and accountable to their users.

Parental involvement in adolescents' social media use

Parents should be involved in their children's social media use to ensure that they are using these platforms safely and responsibly. Parents can monitor their children's online activity, set time limits for social media use, and talk to their children about the risks associated with social media addiction.

Education on responsible social media use

Adolescents need to be educated about responsible social media use so that they can enjoy the benefits of these platforms while avoiding the risks associated with addiction. Education on responsible social media use could include topics such as cyber-bullying, sexting, and privacy breaches.

Research directions for future studies

A content analysis was conducted to answer the fifth research questions “What are the potential research directions for addressing social media addiction in the future?” The study reveals that there is a lack of screening instruments and diagnostic criteria to assess social media addiction. Validated DSM-V-based instruments could shed light on the factors behind social media use disorder. Diagnostic research may be useful in order to understand social media behavioral addiction and gain deeper insights into the factors responsible for psychological stress and psychiatric disorders. In addition to cross-sectional studies, researchers should also conduct longitudinal studies and experiments to assess changes in users' behavior over time ( 20 ).

Another important area to examine is the role of engagement-based ranking and recommendation algorithms in online habit formation. More research is required to ascertain how algorithms determine which content type generates higher user engagement. A clear understanding of the way social media platforms gather content from users and amplify their preferences would lead to the development of a standardized conceptualization of social media usage patterns ( 89 ). This may provide a clearer picture of the factors that lead to problematic social media use and addiction. It has been noted that “misinformation, toxicity, and violent content are inordinately prevalent” in material reshared by users and promoted by social media algorithms ( 90 ).

Additionally, an understanding of engagement-based ranking models and recommendation algorithms is essential in order to implement appropriate public policy measures. To address the specific behavioral concerns created by social media, legislatures must craft appropriate statutes. Thus, future qualitative research to assess engagement based ranking frameworks is extremely necessary in order to provide a broader perspective on social media use and tackle key regulatory gaps. Particular emphasis must be placed on consumer awareness, algorithm bias, privacy issues, ethical platform design, and extraction and monetization of personal data ( 91 ).

From a geographical perspective, the authors have identified some main gaps in the existing knowledge base that uncover the need for further research in certain regions of the world. Accordingly, the authors suggest encouraging more studies on internet and social media addiction in underrepresented regions with high social media penetration rates such as Southeast Asia and South America. In order to draw more contributions from these countries, journals with high impact factors could also make specific calls. This would contribute to educating social media users about platform usage and implement policy changes that support the development of healthy social media practices.

The authors hope that the findings gathered here will serve to fuel interest in this topic and encourage other scholars to investigate social media addiction in other contexts on newer platforms and among wide ranges of sample populations. In light of the rising numbers of people experiencing mental health problems (e.g., depression, anxiety, food disorders, and substance addiction) in recent years, it is likely that the number of papers related to social media addiction and the range of countries covered will rise even further.

Data availability statement

Author contributions.

AP took care of bibliometric analysis and drafting the paper. VB took care of proofreading and adding value to the paper. AS took care of the interpretation of the findings. All authors contributed to the article and approved the submitted version.

Conflict of interest

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

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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How teens and parents approach screen time, most teens at least sometimes feel happy and peaceful when they don’t have their phone, but 44% say this makes them anxious. half of parents say they have looked through their teen’s phone.

An image of a father and teen daughter in discussion while using a smartphone.

Pew Research Center conducted this study to better understand teens’ and parents’ experiences with screen time.

The Center conducted an online survey of 1,453 U.S. teens and parents from Sept. 26 to Oct. 23, 2023, through Ipsos. Ipsos invited one parent from each of a representative set of households with parents of teens in the desired age range from its KnowledgePanel . The KnowledgePanel is a probability-based web panel recruited primarily through national, random sampling of residential addresses. Parents were asked to think about one teen in their household (if there were multiple teens ages 13 to 17 in the household, one was randomly chosen). At the conclusion of the parent’s section, the parent was asked to have this chosen teen come to the computer and complete the survey in private.

The survey is weighted to be representative of two different populations: 1) parents with teens ages 13 to 17 and 2) teens ages 13 to 17 who live with parents. For each of these populations, they survey is weighted to be representative by age, gender, race and ethnicity, household income and other categories.

This research was reviewed and approved by an external institutional review board (IRB), Advarra, an independent committee of experts specializing in helping to protect the rights of research participants.

Here are the questions among parents and among teens used for this report, along with responses, and its methodology .

Today’s teenagers are more digitally connected than ever. Most have access to smartphones and use social media , and nearly half say they are online almost constantly. But how are young people navigating this “always on” environment?

To better understand their experiences, we surveyed both teens and parents on a range of screen time-related topics. Our questions explored the emotions teens tie to their devices, the impact of smartphones on youth, and the challenges parents face when raising children in the digital age.

Key findings from the survey:

Phone-less: 72% of U.S. teens say they often or sometimes feel peaceful when they don’t have their smartphone; 44% say it makes them feel anxious.
Good for hobbies, less so for socialization: 69% of teens say smartphones make it easier for youth to pursue hobbies and interests; fewer (30%) say it helps people their age learn good social skills.
Parental snooping: Half of parents say they have looked through their teen’s phone.
Smartphone standoffs: About four-in-ten parents and teens report regularly arguing with one another about time spent on their phone.
Distracted parenting: Nearly half of teens (46%) say their parent is at least sometimes distracted by their phone when they’re trying to talk to them.

This Pew Research Center survey of 1,453 U.S. teens ages 13 to 17 and their parents was conducted Sept. 26-Oct. 23, 2023. 1

Jump to read about views among teens on: Screen time | Feelings when disconnected from phones | Thoughts on smartphones’ impact

Jump to read about views among parents on: Parenting in the smartphone age | Their own screen time struggles

Teens’ views on screen time and efforts to cut back

Fully 95% of teens have access to a smartphone, and about six-in-ten say they use TikTok, Snapchat or Instagram . But do teens think they spend too much time in front of screens?

A bar chart showing that About 4 in 10 teens say they spend too much time on their phone

More teens say they spend too much time on their phone or social media than say they don’t spend enough time on them. We found that 38% of teens say they spend too much time on their smartphone. About a quarter say the same regarding their social media use. 2

A dot plot chart showing that Teen girls are more likely than boys to say they spend too much time on their phone and social media

But the largest shares say the amount of time they spend on their phone (51%) or on social media (64%) is about right. Relatively few teens say they don’t spend enough time with these technologies.

Views on this differ by gender. Teen girls are more likely than boys to say they spend too much time on their smartphone (44% vs. 33%) or social media (32% vs. 22%).

Teens’ efforts to curb their screen time

A minority of teens have taken steps to reduce their screen time. Roughly four-in-ten teens (39%) say they have cut back on their time on social media. A similar share says the same about their phone (36%).

Still, most teens have not limited their smartphone (63%) or social media (60%) use.

A chart showing that Most teens haven’t cut back on their phone or social media use, but girls are more likely than boys to do so

How teens’ behaviors vary by gender

About four-in-ten or more girls say they have cut back on their smartphone or social media use. For boys, those figures drop to roughly one-third.

How teens’ behaviors vary based on their screen time

Teens who report spending too much time on social media and smartphones are especially likely to report cutting back on each. For instance, roughly six-in-ten teens who say they are on social media too much say they have cut back (57%). This is far higher than the 32% among those who say they are on social media too little or the right amount.

How teens feel when they don’t have their phone

A bar chart showing that Roughly three-quarters of teens at least sometimes feel happy or peaceful when they don’t have their phone; 44% feel anxious

Teens encounter a range of emotions when they don’t have their phones, but we asked them about five specific ones. Roughly three-quarters of teens say it often or sometimes makes them feel happy (74%) or peaceful (72%) when they don’t have their smartphone.

Smaller but notable shares of teens equate not having their phone with more negative emotions. Teens say not having their phone at least sometimes makes them feel anxious (44%), upset (40%) and lonely (39%).

It is worth noting that only a minority of teens – ranging from 7% to 32% – say they often feel these emotions when they’re phone-less.

Teens’ feelings on this differ by some demographic factors:

Age and gender: Older girls ages 15 to 17 (55%) are more likely than younger girls (41%) and teen boys who are younger (41%) and older (40%) to say they feel anxious at least sometimes when they don’t have their smartphone.
Gender: 45% of teen girls say not having their phone makes them feel lonely regularly, compared with 34% of teen boys.

Do teens think smartphones are negatively impacting young people?

As smartphones have become a universal part of teen life, many have asked what impact, if any, phones are having on today’s youth.

Teens shared their perspectives on smartphones’ impact on people their age and whether these devices have made certain aspects of growing up more or less challenging.

A bar chart showing that Most teens say the benefits of smartphones outweigh the harms for people their age

Most teens think the benefits of smartphones outweigh the harms for people their age. Seven-in-ten teens say smartphones provide more benefits than harms for people their age, while a smaller share (30%) take the opposing view, saying there are more harms than benefits.

Teens’ views, by gender and age

Younger girls ages 13 and 14 (39%) are more likely than older teen girls (29%) and teen boys who are younger (29%) and older (25%) to say that the harms of people their age using smartphones outweigh the benefits.

The survey also shows that teens see these devices’ impacts on specific aspects of life differently.

More teens believe smartphones make it easier, rather than harder, to be creative, pursue hobbies and do well in school. Majorities of teens say smartphones make it a little or a lot easier for people their age to pursue hobbies and interests (69%) and be creative (65%). Close to half (45%) say these devices have made it easier for youth to do well in school.

About two-thirds of teens say phones make it easier for youth to pursue interests, be creative; fewer think it helps peers learn good social skills

Views are more mixed when it comes to developing healthy friendships. Roughly four-in-ten teens say smartphones make it easier for teens to develop healthy friendships, while 31% each say they make it harder or neither easier nor harder.

But they think smartphones have a more negative than positive impact on teens’ social skills. A larger percentage of teens say smartphones make learning good social skills harder (42%) rather than easier (30%). About three-in-ten say it neither helps nor hurts.

How parents navigate raising teens in the smartphone age

With the rise of smartphones, today’s parents must tackle many questions that previous generations did not. How closely should you monitor their phone use? How much screen time is too much? And how often do phones lead to disagreements?

We developed a set of parallel questions to understand the perspectives of both parents and teens. Here’s what we found:

A bar chart Half of parents look through their teen’s phone; 43% of teens think their parent checks their phone

It’s common for parents to look through their teen’s phone – and many of their teens know it. Half of parents of teens say they look through their teen’s phone. When we asked teens if they thought their parents ever look through their phones, 43% believed this had happened.

Whether parents report looking through their child’s smartphone depends on their kid’s age. While 64% of parents of 13- to 14-year-olds say they look through their teen’s smartphone, this share drops to 41% among parents of 15- to 17-year-olds.

Teens’ accounts of this also vary depending on their age: 56% of 13- to 14-year-olds say their parent checks their smartphone, compared with 35% of teens ages 15 to 17.

How often do parents and teens argue about phone time?

A bar chart showing that About 4 in 10 parents and teens say the time teens spend on their phone regularly leads to arguments

Parents and teens are equally likely to say they argue about phone use. Roughly four-in-ten parents and teens (38% each) say they at least sometimes argue with each other about how much time their teen spends on the phone. This includes 10% in each group who say this happens often .

Still, others say they never have these types of disagreements. One-quarter of parents say they never argue with their teen about this, while 31% of teens say the same.

Teens’ and parents’ views, by race and ethnicity

Hispanic Americans stand out for reporting having these disagreements often. While 16% of Hispanic teens say they often argue with their parent about how much time they’re spending on their phone, that share drops to 9% for White teens and 6% for Black teens. 3

A similar pattern is present among parents. Hispanic parents (19%) are more likely than White (6%) or Black (7%) parents to say they often argue with their teen about this.

Teens’ views, by frequency of internet use

The amount of time teens report being online is also a factor. About half (47%) of teens who report being online almost constantly say they at least sometimes argue with their parent about the amount of time they spend on their phone, compared with those who are online less often (30%).

How much do parents prioritize tracking their teen’s phone use?

A bar chart showing that Most parents say managing how much time their teen is on the phone is a priority

Most parents prioritize managing the amount of time their teen spends on the phone. Roughly three-quarters of parents (76%) say managing how much time their teen spends on the phone is an important or a top priority. Still, 19% of parents don’t consider this a priority.

Parents’ views, by race and ethnicity

Majorities of parents across racial and ethnic groups think of this as a priority. But some groups stand out for how much they prioritize this. For example, Hispanic (25%) or Black (24%) parents are more likely to say managing how much time their teen is on the phone is a top priority. That share drops to 10% among White parents.

Parents’ views, by household income

We also see differences between the lowest and highest income households: 22% of parents whose annual household income is less than $30,000 consider managing the amount of time their teen is on the phone a top priority, compared with 14% of those whose household income is $75,000 or more a year. Those whose household income is $30,000 to $74,999 a year do not meaningfully differ from either group.

Do parents set time limits on their teen’s phone use?

A split bar chart showing that Parents with younger teens are more likely to set time limits on phone use

There’s a nearly even split between parents who restrict their teen’s time on their phone and those who don’t. About half of parents (47%) say they limit the amount of time their teen can be on their phone, while a similar share (48%) don’t do this.

Parents’ views, by teen’s age

Parents of younger teens are far more likely to regulate their child’s screen time. While 62% of parents of 13- to 14-year-olds say they limit how much time their teen can be on their phone, that share drops to 37% among those with a 15- to 17-year-old.

How difficult is it for parents to keep up with their teen’s phone use?

A chart showing that Higher-income parents are more likely to say it’s hard to manage how much time their teen is on the phone

Managing screen time can feel like an uphill battle for some parents. About four-in-ten say it’s hard to manage how much time their teen spends on their phone. A smaller share (26%) says this is easy to do.

Another 26% of parents fall in the middle – saying it’s neither easy nor hard.

Higher-income parents are more likely to find it difficult to manage their teen’s phone time. Roughly half (47%) of parents living in households earning $75,000 or more a year say managing the amount of time their teen is on their phone is hard. These shares are smaller among parents whose annual household income falls below $30,000 (38%) or is between $30,000 and $74,999 (32%).

Parents’ own struggles with device distractions, screen time

Teens aren’t the only ones who can be glued to their phones. Parents, too, can find themselves in an endless cycle of checking emails , text messages and social media.

With that in mind, we asked parents to think about their own screen time – both the time they spend on their phone, and if it ever gets in the way of connecting with their teen.

Do parents think they spend too much time on their phone?

A bar chart Roughly half of parents say they spend too much time on their phone, but this varies by income

Like teens, parents are far more likely to say they spend too much rather than not enough time on their phone. About half of parents (47%) say they spend too much time on their smartphone. Just 5% think they spend too little time on it. And 45% believe they spend the right amount of time on their phone.

Parents’ views differ by:

Household Income: 50% of parents with annual household incomes of $75,000 or more say they spend too much time on their phone. This share drops to 41% among those living in households earning $30,000 to $74,999 a year and 38% among those earning under $30,000.
Race and ethnicity: 57% of White parents believe they spend too much time on their phone, compared with 38% of Black parents and 34% of Hispanic parents.

How often are parents distracted by their phone when talking with their teen?

A bar chart showing that Nearly half of teens say their parent at least sometimes gets distracted by their phone in conversations; fewer parents see it this way

When it comes to distracted parenting, parents paint a rosier picture than teens. Nearly half of teens (46%) say their parent is at least sometimes distracted by their phone when they’re trying to talk to them, including 8% who say this happens often.

But when parents were asked to assess their own behavior, fewer – 31% – say this happens regularly.

Throughout this report, “teens” refers to those ages 13 to 17 and “parents” refers to those with a child ages 13 to 17. ↩
A 2018 Center survey also asked U.S teens some of the same questions about experiences and views related to smartphone and social media. Direct comparisons cannot be made across the two surveys due to mode, sampling and recruitment differences. Please read the Methodology section to learn more about how the current survey was conducted. ↩
There were not enough Asian respondents in the sample to be broken out into a separate analysis. As always, their responses are incorporated into the general population figures throughout the report. ↩

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Table of contents, teens and internet, device access fact sheet, teens and social media fact sheet, a declining share of adults, and few teens, support a u.s. tiktok ban, teens, social media and technology 2023, about 1 in 5 u.s. teens who’ve heard of chatgpt have used it for schoolwork, most popular.

About Pew Research Center Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of The Pew Charitable Trusts .

What is an event survey, types of event survey questions, general event survey questions, survey questions for event attendees, survey questions for event volunteers, survey questions for sponsors and partners, survey questions for speakers and vips, survey questions for employees, survey questions for virtual events, 14 survey questions for hybrid event attendees, sponsors, and exhibitors, key takeaways: do more with event survey question data, 51 event survey questions you need to ask for the best insights.

Get inside the minds of your attendees and other stakeholders with these 51 must-ask event survey questions for virtual, in-person, and hybrid events.

What do your attendees think about your event? How about sponsors? Are they likely to support your event next year? What was the experience like for in-person versus virtual attendees at your hybrid event?

It’s hard to measure how well an event went when you only have your own experience to guide you. That’s why event tools like event surveys and event evaluations are critical for measuring attendee satisfaction. Pre-event and post-event survey questions help you gather important stakeholder feedback that would otherwise get lost in the shuffle or never shared at all. You can pair the insights you gain from event surveys with event KPIs pulled from your event platform to create a fully developed picture of how successful your event was, and how you can improve it in the future.

Don’t forget: All feedback is good feedback. Although negative feedback can sting, it’s essential for optimizing your event strategy and delivering the kinds of event experiences your attendees need, want, and expect. In this article, you’ll find event survey questions of all varieties to help you measure success and deliver the best events possible.

Event surveys are questionnaires designed to collect feedback from your attendees and can include a combination of multiple-choice and open-ended questions. You can send surveys to participants before, during, or after the event, and they are often shared digitally. Any person who interacted with your event should receive a survey because sponsors, attendees, and your event staff will all have unique perspectives on different aspects of your event.

Successful event strategies depend on stakeholder satisfaction and event surveys are one of the best ways to measure this. Whether your goal is to build a case for pitching event sponsors, to create a great virtual event experience, or to improve attendee experience on the fly, event surveys lift the curtain and give organizers insight into how attendees feel.

There are several different ways that you can pose questions to stakeholders, including the following:

NPS Questions: A multiple-choice question that asks participants to rate an item on a numeric scale. The resulting values determine the net promoter score ( NPS )
Yes-no Questions: A binary question that is often followed by an open-ended question based on conditional logic
Open-ended Questions: While harder to analyze en-masse, open-ended questions can provide valuable qualitative feedback

Net Promoter Score - Event Survey Questions

In this post, we’ll indicate whether each question functions best as an NPS question, Yes-no question, or open-ended qualitative question. These Question Type suggestions are just that — suggestions, it’s up to you to determine the best use for your event survey.

Read on to see 51 great event survey questions and how they can help you better evaluate your event.

1. What is your level of satisfaction with this event?

Question Type: NPS

Survey questions like this one are pretty straightforward. It’s a good starting point for the questions that follow and allows you to get the big picture idea of how the event went in general and if it met expectations. A best practice in event surveys is to start off more general and get more granular towards the end.

2. Which elements of the event did you like the most?

Question Type: Open-ended

Questions like this help you get an idea of what is worth repeating for future iterations of the event. Keep track of each point and tally the number of times it was mentioned. Rank them in order from most votes to least and prioritize the winners next year.

3. What, if anything, did you dislike about this event?

Although you may be hesitant to ask this question, knowing your shortcomings allows you to learn from them. Don’t write a survey that forces respondents to leave a glowing review. Instead, show them how much you value their opinion and display those changes at your next event.

4. Are you likely to participate in one of our events in the future?

This one is very important because it reveals how enthusiastic the survey participant is about your event. Compare these numbers to the actual number of attendees who come back next year. While plans do change, you should ideally see the majority of them return. If not, consider what adjustments need to be made.

5. How likely are you to tell a friend about this event?

Using an NPS to inquire about referrals is another great way to measure event success. While some people may have enjoyed the event themselves, the true test of their experience is to see whether or not they’d subject a friend to it. Follow up on positive responses to this question with referral links and special offers.

6. Is there anything else you would like us to know?

Open-ended questions allow participants to give you feedback on anything your event survey may not have covered. You won’t be able to cover every aspect of the event in the survey. This question serves as a catchall for any additional feedback.

7. Why did you choose to attend our event and what are you hoping to take away from the experience?

Use this question before the event to make schedule adjustments or other tweaks that magnify the most coveted aspects of the experience. Give the people what they want and show them that your focus is truly on their experience

8. What did you most enjoy about today?

This is a great question for multi-day events. Remember to address any concerns or negative feedback personally and do your best to apply the feedback for the following days. Multi-day events present a unique opportunity to improve your event before it’s even over.

9. Please indicate your satisfaction with the following aspects of the event:

Venue/ Event Platform
Quality of Sessions
Amount of Sessions Offered
Date(s) of Event

All of these big-picture event characteristics shape the experience for attendees. You may find some surprising insights for the next time you plan an event. And because all of these factors are within your control, the changes will be easy to make and measure in the future.

Note: In the era of hybrid events, the virtual event platform you use to power your experience is the venue. As a result, you should be evaluating the experience of attendees in navigating it similar to how you would ask an attendee to rate a traditional venue.

10. How satisfied were you with the networking opportunities provided?

Networking is a key element of events, but with the rise of virtual events, networking has become more complicated. According to the Evolution of Events Report , 68.8% of event marketers believe it is more difficult to provide networking opportunities when hosting a virtual event. Ask this event survey question to make sure you have found the right solution for your attendees. Be sure to have a text box along with the NPS rating so participants can elaborate on their experiences.

11. Did you have any issues registering for or attending this event?

Question Type: Yes-no

This event survey question can illuminate areas where your event platform or registration software may not be a user-friendly experience and causes frustration with attendees. If you realize there is a pattern in the responses, talk to your event platform provider or user-experience team to improve on the experience. The last thing you want is for attendees to have trouble even accessing the event because it sets the tone for the rest of the event.

12. How satisfied were you with the speakers and sessions at our event?

Attendee satisfaction is one of the key indicators that people will come back to your events. Making sure your speakers and sessions were interesting and valuable is a top priority to ensure attendees were satisfied with the experience. Questions like this one help you get an idea of what is worth repeating for future events.

13. What topics would you like to see more of at our next event?

Your post-event survey can be a launching point for ideas for your next event. Attendees may have suggestions and interesting perspectives you otherwise wouldn’t have known. Ask attendees what they want to see and design your next event with their feedback in mind.

14. Were you happy with the time for discussion during sessions?

We’ve all been to an event where the session ran out of time leaving nothing for discussion, and quite frankly, it’s a letdown. If attendees felt like there was not enough time, consider carving out more time for attendees to participate in the discussion.

15. How did you feel about the duration of the content?

Content length is especially important for virtual events. Attention spans are getting shorter and tuning in from home provides a plethora of distractions. In our Virtual Benchmarks Report , we found the average virtual attendee only watches 68% of a virtual session that is 20 minutes or longer. That comes out to just over 13 minutes. By asking this event survey question you can gauge if your sessions were the appropriate length for your audience or use the insights to take action to improve durations for the next event.

16. How did you hear about this event?

The main objective of this question is to find out where attendees first heard about your event. Use the information you gather from this event survey question to see what marketing channels are working the best for your event, and where you need to improve.

17. Would you recommend this event as a positive volunteer opportunity to your network?

Similar to attendees, your volunteers often represent the backbone of your event. Knowing that they enjoyed the experience enough to recommend future volunteers should be gratifying. Plus, there usually aren’t enough volunteers to go around, so having some people to follow up with could help build out your team.

18. Are you interested in volunteering with us in the future?

If volunteers are willing to come back again then you know you’ve thrown a great event. Keep a list of these names and calculate how many volunteers you’ll need for next year.

19. Please share your thoughts on the event as a whole.

This open-ended question shows sponsors and partners that you value their opinion as collaborators. You’ll also want to start with a broad question like this one because it will help them think critically about the details in the following points.

20. Did this year’s event meet your expectations? Why or why not?

Question Type: Yes-no, Open-ended

While you may already know their goals, you might not know what they were expecting from this event. Generally speaking, it’s often hard for anyone to gauge their assumptions about an experience until it is over, which is why including this question along with a prompt to further explain their answer is often more insightful than simply checking yes or no.

21. How relevant was the audience for your business/industry?

Question: NPS

To create a great sponsor partnership, you need to ensure the event audience is relevant to sponsors. Often brands sign up to sponsor events to achieve sales and marketing goals, or brand visibility. If the audience is not relevant, sponsors will have less success engaging with attendees and fall flat on their goals.

22. What was the ROI of sponsoring this event?

This question will give you a good idea of if your sponsorship packages were valuable or not. Keeping the question opened ended will help educate you on exactly what the sponsors found valuable. If the responses are good and the event ROI was high, you could also use these answers as proof demonstrating to future sponsors your sponsorship opportunities are a great investment.

Bonus Tip: According to our Event Marketing Report , 54% of event marketers have trouble showing event ROI to key decision-makers. Make sure to give your sponsors plenty of data to help them track ROI and make sure their event sponsorship made an impact.

23. Will we see you again next year?

Ideally, all of your sponsors and partners would love to do the event every year. Be sure to do a pulse check and determine if their experience of the event was all they’d hoped it would be. Follow up with no responses for more information as to why they won’t be returning.

24. Did you receive all the information you needed to successfully present before the event?

Preparation is a key element to any presentation’s success. By asking your speakers if they felt they had the information needed to successfully present you can identify strengths and weaknesses in your speaker preparation. If a speaker answers no, be sure to personally follow up with them to get more information, not only will they feel heard but you will gain invaluable insight into how to create a better experience next time.

25. How would you rate our event venue and equipment in regards to how it served your keynote?

For in-person events, speakers are the most concerned with the elements of the venue that either enhance or detract from their presentation. No one else can give you a better idea of venue effectiveness the way a speaker can. You can modify this question for virtual and hybrid events as well. For example “How would you rate working with our production team and virtual platform?”

26. Is there anything we could have done to make your event experience easier or more convenient?

This is especially important for the VIPs you hope to impress. Cater to their needs and ensure their continued involvement for years to come.

27. Do you have a friend or colleague who would enjoy speaking at our future events?

Speakers are often very involved in their communities and networks and surround themselves with pros in their field. You can easily source new and fresh presenters for next year from this group. And with the recommendation of someone who has already done it, the decision will be a no-brainer for them.

28. How would you rate the organization of this event?

Your team will be intimately familiar with the cogs of your event. If they were confused or unclear about what was happening during the event, your entire system might need a total revamp. If they felt comfortable and empowered for the duration of the event then you have a strong model to replicate in the future.

29. Do you feel roles were clearly communicated?

To have a successful event team experience you must have clear roles and responsibilities. If roles aren’t clear it can lead to problems and miscommunications that impact the execution of your event. Asking your team for feedback will let you know if there are areas to improve in team communication next event.

30. Do you think the event met its goals?

This question is a warm-up for the following. Reflecting as a team on event goals will give you a greater sense of whether you accomplished your event goals or not.

31. What impact do you see this event having on your immediate business goals?

Make sure to tie your event back into your main mission statement by asking employees to directly reflect on the impact it has had on what they’re trying to accomplish at this moment in time. If you don’t connect the event evaluation to the greater objective or plan, the event itself can feel isolated and unnecessary. Asking fellow employees to put the benefits into their own words reinforces their positive experience at the event and secures its slot in the marketing budget for next year.

32. Are you satisfied with the results of this event in regards to the impact it has made on your department?

Zooming back out again, employees should consider how the actions of the marketing department directly affect their greater purpose in the company. Asking this question will even help you learn and make connections between how your event can (and should) support the company as a whole.

33. How satisfied were you with the platform experience?

Your virtual platform can make or break your event. Asking this question allows you to find out how attendees felt about the overall virtual experience. Make sure to include a prompt with room to add more in case participants wish to elaborate.

34. What features did you like best about the event experience?

Questions like this allow you to narrow in on those experiences while planning your next event. Knowing what worked and what is worth repeating saves you time when producing your next event. Keep a list of each point and find themes and popular responses to prioritize popular experiences next year.

35. Did you find the event easy to navigate?

Success at a virtual event goes hand-in-hand with how easily attendees can navigate the experience. If attendees can’t find parts of the event due to a poor navigation design, they won’t be able to experience the event in full. This question will gauge if any improvements need to be made in the next iterations.

36. If you used tech support, how would you rate your experience?

When an attendee runs into an issue attending your virtual event, they contact your support team. Can’t log in? Contact event support. No audio? Contact event support. How the issue is resolved will leave a lasting impression. No matter if you have live chat, email, or a knowledge base this question will help give you insight into if your current tech support system is working or not.

37. How would you rate the quality of audio and video at the event?

There are many variables when it comes to audio and video at virtual events. Many speakers are presenting from their homes which leaves room for poor internet connections, bad audio quality, or less than stellar backgrounds. Ask attendees to rate the quality of audio and video. If attendees weren’t satisfied, do an AV audit and identify areas of improvement, then relay that information to speakers and presenters at the following event. Improvements might include minimum internet speeds, types of approved microphones, or sending presenter kits directly to speaker’s homes to ensure quality audio and visual.

Although many of the questions above can be altered for a hybrid audience, we wanted to break out some questions specifically for hybrid events. Below, you’ll find questions followed by the type of question.

Hybrid Event Survey Questions for Both Audiences

Did you participate in the event virtually or in-person? (Multiple-choice: Virtual, In-person)
Were the before, during, and post-event communications clear? (Yes-no)
Were you able to effectively network in a hybrid environment? (Yes-no)
How would you prefer to attend your next hybrid event? ( Multiple choice: Virtual, In-person, No preference)

Hybrid Event Survey Questions for Virtual Attendees

Pre-event question: As a virtual attendee, do you want the opportunity to engage with in-person attendees? (Yes-no)
Why did you choose to participate virtually rather than attend in-person? ( Open-ended)
As a virtual attendee, do you feel like you were part of the live experience? (Yes-no)
Do you feel not attending the event onsite hindered your overall experience? (Yes-no)

Note: This pre-event question allows you to provide different options in the future or to change plans before the event kicks off.

Hybrid Event Survey Questions for In-Person Attendees

How many virtual attendees did you engage with? ( Multiple-choice)
How would you rate your experience talking to virtual attendees? (NPS)
Why did you choose to attend in-person? (Open-ended)
What types of on-site activities would you enjoy in the future? (Open-ended)

Hybrid Event Survey Questions for Sponsors and Exhibitors

As a sponsor, which format did you prefer to engage with attendees? ( Multiple choice: Virtual, In-person, Both)
As an exhibitor, did you have the resources to effectively manage both an in-person and virtual booth at the same time? (Yes-no)

Event engagement is so much more than selling tickets. With the help of event survey tools you can get to the core of the question, “How do I know if my event was successful?” and see if your event was a success. When crafting your surveys, keep these general ideas in mind:

Feedback is good. Every participant in your event, whether they are involved behind the scenes or on the front-end, has something valuable to teach you.
People love to share their opinion , an event survey gives them a platform to do so and feel valued.
Find your people. By knowing who you’ve won over this year you’ll already have a jump start on making next year even more successful.
Keep it short. While it would be great to ask all the questions mentioned above, be respectful of participants’ time and keep your survey short.
If you don’t know, just ask . People love helping others (and talking about themselves), so chances are they’ll be more than willing to share their experience with you.

Editor’s Note: This post was originally published in November 2018 and has been updated for relevance.

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The intermittent fasting trend may pose risks to your heart

Intermittent fasting — when people only eat at certain times of day — has exploded in popularity in recent years. But now a surprising new study suggests that there might be reason to be cautious: It found that some intermittent fasters were more likely to die of heart disease.

The findings were presented Monday at an American Heart Association meeting in Chicago and focused on a popular version of intermittent fasting that involves eating all your meals in just eight hours or less — resulting in at least a 16-hour daily fast, commonly known as “time-restricted” eating.

The study analyzed data on the dietary habits of 20,000 adults across the United States who were followed from 2003 to 2018. They found that people who adhered to the eight-hour eating plan had a 91 percent higher risk of dying from heart disease compared to people who followed a more traditional dietary pattern of eating their food across 12 to 16 hours each day.

The scientists found that this increased risk also applied to people who were already living with a chronic disease or cancer. People with existing cardiovascular disease who followed a time-restricted eating pattern had a 66 percent higher risk of dying from heart disease or a stroke. Those who had cancer meanwhile were more likely to die of the disease if they followed a time-restricted diet compared to people with cancer who followed an eating duration of at least 16 hours a day.

The study results suggest that people who practice intermittent fasting for long periods of time, particularly those with existing heart conditions or cancer, should be “extremely cautious,” said Victor Wenze Zhong, the lead author and the chair of the department of epidemiology and biostatistics at the Shanghai Jiao Tong University School of Medicine in China.

“Based on the evidence as of now, focusing on what people eat appears to be more important than focusing on the time when they eat,” he added.

Zhong said that he and his colleagues conducted the new study because they wanted to see how eating in a narrow window each day would impact “hard endpoints” such as heart disease and mortality. He said that they were surprised by their findings.

“We had expected that long-term adoption of eight-hour time restricted eating would be associated with a lower risk of cardiovascular death and even all-cause death,” he said.

Losing lean muscle mass

The data didn’t explain why time-restricted eating increased a person’s health risks. But the researchers did find that people who followed a 16:8 time-restricted eating pattern, where they eat during an eight-hour window and fast for 16, had less lean muscle mass compared to people who ate throughout longer periods of the day. That lines up with a previous clinical trial published in JAMA Internal Medicine , which found that people assigned to follow a time-restricted diet for three months lost more muscle than a control group that was not assigned to do intermittent fasting.

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Holding onto muscle as you age is important. It protects you against falls and disability and can boost your metabolic health. Studies have found that having low muscle mass is linked to higher mortality rates, including a higher risk of dying from heart disease, said Zhong.

He stressed that the findings were not definitive. The study uncovered a correlation between time-restricted eating and increased mortality, but it could not show cause and effect. It’s possible for example that people who restricted their food intake to an eight-hour daily window had other habits or risk factors that might explain their increased likelihood of dying from heart disease. The scientists also noted that the study relied on self-reported dietary information. It’s also possible that the participants did not always accurately report their eating durations.

A trendy form of dieting and weight control

Intermittent fasting has been widely touted by celebrities and health experts who say it produces weight loss and a variety of health benefits. Another form of intermittent fasting involves alternating fasting days with days of eating normally. Some people follow the 5:2 diet, in which they eat normally for five days a week and then fast for two days.

But time-restricted eating is generally considered the easiest form of intermittent fasting for people to follow because it doesn’t require full-day fasts. It also typically doesn’t involve excessive food restriction. Adherents often eat or drink whatever they want during the eight-hour eating period — the only rule is that they don’t eat at other times of day.

Some of the earliest studies on time-restricted eating found that it helped prevent mice from developing obesity and metabolic syndrome. These were followed by mostly small clinical trials in humans, some of which showed that time-restricted eating helped people lose weight and improve their blood pressure , blood sugar and cholesterol levels. These studies were largely short-term, typically lasting one to three months, and in some cases showed no benefit .

One of the most rigorous studies of time-restricted eating was published in the New England Journal of Medicine in 2022. It found that people with obesity who were assigned to follow a low-calorie diet and instructed to eat only between the hours of 8 a.m. and 4 p.m. daily lost no more weight than people who ate the same number of calories throughout the day with no restrictions on when they could eat. The two diets had similar effects on blood pressure, blood sugar, cholesterol, and other metabolic markers.

The findings suggest that any benefits of time-restricted eating likely result from eating fewer calories.

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MRA Guide to the Top 16 Social Media Research Questions

What is Social Media?

What is Social Media Research?

THE ROLE OF SOCIAL MEDIA RESEARCH

#2. What data sources are typically used in SMR?

#3. How does SMR interact with other forms of traditional and non-traditional research, including online, offline, in-person, and qualitative and quantitative?

#4. How reliable are SMR results?

#5. Within businesses and organizations, how will SMR activities be tracked and aggregated, and whose responsibility is it to handle each of those functions?

#6. What additional knowledge, skills, and abilities will a corporate researcher need to learn in order to improve their level of competency with SMR?

#7. Are the participants aware that their usergenerated content is under observation?

Ethical and Legal Issues

#9. What are the controversies and legal issues regarding the rights of the people whose data is being used?

SM Research Processes & Providers

#11. What are the standard data and/or research outputs?

#12. What is the process for gathering data?

#13. What data quality processes are implemented in each stage of the SMR?

#14. Does the company provide sentiment scoring?

#15. If sentiment scoring is provided, what is the process for validating results?

#16. What, if any, methods are used for determining the geography associated with the data?

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The SAGE Handbook of Social Media Research Methods

Subject index

Front Matter

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The effect of social media on well-being differs from adolescent to adolescent

Similar content being viewed by others

Some socially poor but also some socially rich adolescents feel closer to their friends after using social media

Associations between youth’s daily social media use and well-being are mediated by upward comparisons

Variation in social media sensitivity across people and contexts

Introduction

Person-specific effects

Social media and affective well-being

Average and person-specific effects

Overall social media use.

Instagram use

WhatsApp use

Limitations and directions for future research

Participants

Frequency of social media use

Duration of social media use