Social media platforms, which are becoming a primary news source for many individuals, can quickly spread misinformation faster than ever before. These information disorders may contribute to increased polarization and extremism, possibly undermining democracy and trust in public institutions worldwide. Because of this growing problem, researchers have begun investigating the effectiveness of possible interventions to counter this misinformation. This research is critical given the many societal challenges we face that are associated with the spread of false or misleading information.

Most research in the countermeasures space focuses on the effectiveness of some more easily studied interventions. Some interventions, like fact-checking, are studied more than others because they can be evaluated without complete access to comprehensive social media data. Most researchers also focus on assessing the effectiveness of an intervention without considering whether the public would support the countermeasure. Platforms and governments will likely only implement changes that have public support.

In this thesis, I develop a framework for designing and evaluating misinformation interventions that integrates current research on effectiveness with user acceptance to enable more effective implementation strategies. To accomplish this task, I created a detailed categorization of interventions. Then, I conducted a citation network analysis of the literature in this field to identify research gaps. I administered a comprehensive survey asking the American public about their social media behavior and opinions on various interventions. The survey also examines how certain factors may influence user acceptance, including the perceived effectiveness, fairness, and intrusiveness of each intervention. Next, I developed a training effort to assess whether media literacy can improve an individual’s willingness and ability to counter misinformation. Finally, I combine this research with the professional opinions of expert researchers in this field to evaluate countermeasures, aiming to identify the shared features that make interventions both effective and practical.

289 pages

Thesis Committee:
Kathleen M. Carley (Chair)
Hong Shen
Chris Labash
Pablo Barberá (University of Southern California/Meta)

Nicolas Christin, Head, Software and Societal Systems Department
Martial Hebert, Dean, School of Computer Science

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