Curtailing False News, Amplifying Truth: Evaluating Anti-Misinformation Measures on Social Media with Sergei Guriev, Emeric Henry and Ekaterina Zhuravskaya

We develop a unified framework to evaluate policy measures aimed at reducing the circulation of false news on social media, such as raising awareness of the dangers of misinformation, offering fact-checking, requiring confirmation clicks, and asking users to think about the content they are about the share. We evaluate the impact of these interventions on the sharing of false and true political news on Twitter using a randomized experiment during the 2022 mid-term U.S. elections. We find that priming users about the reputational costs of sharing misinformation is the most effective policy in changing the balance of shared news towards true content. We build a model of sharing decisions, where a sharer derives utility from persuading the audience, signaling their partisan affiliation, and from maintaining reputation as a credible source. In equilibrium, sharing depends on the perceived veracity and partisanship of content, the salience of reputational concerns, and sharing frictions. Structural estimation of this relationship allows us to shed light on the mechanisms through which different policy interventions affect circulation of false and true content on social media. The impact of all considered policies comes mostly from their effects on the salience of reputation and on the sharing frictions. The effect policies have on the perceived veracity of content plays a negligible role in their impact on sharing, even when it comes to fact-checking. Priming intervention performs the best because it is designed to affect salience with minimal added frictions.