Do Fact-Checks Slow the Spread of Misinformation on Facebook and Twitter?

Harvard University

Abstract

A great deal of time and energy have been invested in fact-checking as a way of countering misinformation and false beliefs. Yet it remains unclear whether fact-checking actually decreases the influence of misinformation. Numerous lab-based and online experiments on fact-checking suggest that it can reduce belief in false claims. However, these studies examine the effects of fact-checks on individual-level cognition under artificial conditions. The dearth of population-level studies has left many important questions unanswered, and consequently, the efficacy of fact-checking in a real-world setting is still unclear. To fill this gap, this proposal aims to understand the efficacy of fact-checking at a societal level. We propose a study using historical Facebook and Twitter data that will examine four key research questions:

  1. In the days following the release of fact-checks, do shares of claims labeled false taper off on Facebook and Twitter?
  2. How are the effects of fact-checks on related claims mediated by sharer and sharer-friend ideology, region, and demographics?
  3. Does fact-checking affect the likelihood of a claim to recirculate?
  4. How does the distribution of Facebook user reactions to claims and fact-checks change over time, and do they interact?

Research Team

Principal Investigator

Matthew Baum

Marvin Kalb Professor of Global Communications, Professor of Public Policy, Harvard University

  • Bio ▾

    Matthew A. Baum (PhD, UC San Diego, 2000) is the Marvin Kalb Professor of Global Communications and professor of public policy at the Harvard Kennedy School. Dr. Baum's research focuses on the role of the mass media and public opinion in contemporary American politics and foreign policy, as well as on the role of misinformation in American politics. He conceived and co-organized a scholarly conference on fake news and misinformation at Harvard University in February 2017, entitled “Combating Fake News.” He is also creator of the “Combating Fake News” Google Group, which serves as a collaborative hub and intellectual sounding board for over 500 researchers interested in this substantive area. He is also co-lead-author of “The Science of Fake News,” which appeared in Science in March 2018, and currently serves as a member of the American Region subcommittee of the Social Science One project. His research has been published in over a dozen scholarly journals, such as the American Political Science Review, American Journal of Political Science, Journal of Politics, and International Organization.

Participants

Nicholas Beauchamp

Assistant Professor of Political Science, Northeastern University

  • Bio ▾

    Nicholas Beauchamp is an assistant professor of political science at Northeastern University. He received his PhD from the NYU Department of Politics in September 2012, specializing in US politics (political behavior, campaigns, opinion, political psychology, social media) and political methodology (quantitative text analysis, machine learning, Bayesian methods, agent-based models, networks). His dissertation develops new techniques in text analysis to model the interplay between speech, belief, and behavior in legislatures, campaign advertising, and online communication. His current research projects examine argument and long-term opinion change online, the spread and evolution of ideas over Twitter, and predicting and explaining Supreme Court decisions using the text of legal briefs.

Nic Dias

Researcher, Harvard University

  • Bio ▾

    Nic Dias is a researcher at the Harvard Kennedy School’s Shorenstein Center. He leads scientific research undertaken by the center’s anti-misinformation initiative, the Information Disorder (ID) Lab, and helps devise the social monitoring workflows that power the lab. Dias’s research interests include how mis- and disinformation spread online, the effective correction of false beliefs, and how individuals and groups make content moderation decisions. He uses a variety of research methods including experiments, surveys, interviews, focus groups, and computational techniques.

Nir Grinberg

Postdoctoral Researcher, Northeastern University

  • Bio ▾

    Nir Grinberg is a research fellow at the Harvard Institute for Quantitative Social Science (IQSS) jointly with the Lazer Lab at the Network Science Institute of Northeastern University. He completed his PhD in computer science at Cornell University under the supervision of Professor Mor Naaman as part of the Jacobs Institute at Cornell Tech. During his PhD he interned at Facebook (twice), Yahoo! Labs, SocialFlow, and Bloomberg. Prior to Cornell, he received an MS in computer science from Rutgers University and a double major BSc in physics and computer science from Tel-Aviv University. In his research, he combines machine learning, natural language processing, and statistical methods to learn about human behavior in the real world using large-scale datasets. The principal goal of his research is to influence system design to enable people to allocate their attention more efficiently and effectively. His dissertation focused on computational methods in the study of individuals' attention online, for example to digital news or social media.

Cameron Hickey

Technology Manager, Harvard University

  • Bio ▾

    Cameron Hickey is an Emmy Award–winning journalist, cinematographer, and software developer and has covered science and technology for thePBS NewsHour with correspondent Miles O’Brien for the last 10 years. Since the 2016 election, he has focused on building tools to investigate misinformation on social media. At the Shorenstein Center at Harvard’s Kennedy School, Hickey leads the Information Disorder Lab, a research project focused on monitoring, investigating, and analyzing problematic content online.

David Lazer

Distinguished Professor of Political Science and Computer and Information Science, Northeastern University

  • Bio ▾

    David Lazer is a professor of political science and computer and information science and the codirector of the NULab for Texts, Maps, and Networks. Before joining the Northeastern faculty in fall 2009, he was an associate professor of public policy at Harvard’s John F. Kennedy School of Government and director of its Program on Networked Governance. He holds a PhD in political science from the University of Michigan. Professor Lazer’s research centers on social networks; governance, or how the patterns of institutional relations yield functional or dysfunctional systems; and technology and its use in communication. An authority on social networks, he has written several papers on the diffusion of information among interest groups and between these groups and the government. He is the coeditor of Governance and Information Technology: From Electronic Government to Information Government and has also written extensively on the use of DNA in the criminal justice system.

Briony Swire-Thompson

Postdoctoral Researcher, Northeastern University

  • Bio ▾

    Briony Swire-Thompson is a postdoctoral researcher at Northeastern University’s Network Science Institute and a fellow at the Harvard Institute for Quantitative Social Sciences. Her research investigates what drives belief in inaccurate information, why certain individuals are predisposed to refrain from belief change even in the face of corrective evidence, and how corrections can be designed to maximize impact. Swire-Thompson’s PhD is in psychological science. Prior to joining Professor Lazer’s lab, she was with the Cognitive Science Laboratories at the University of Western Australia and was a Fulbright scholar at the Massachusetts Institute of Technology’s Political Science Department.

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