Abstract
Using an online randomized experiment in the context of the 2022 US midterm elections, we compare the welfare impact of different policies proposed to fight the circulation of false news. We exposed a random sample of Twitter users to a series of 4 Tweets, two true and two false, and allowed them to share at most one. The participants were randomly allocated to different policies, standard in the literature: a control group, a fact check treatment, a policy priming accuracy, and a policy requiring an extra click. The reduced form evidence shows that priming accuracy performs best: it decreases sharing of false news and increases the circulation of true news. A structural model of sharing shows that the effect of the policies can be decomposed into three channels: priming accuracy decreases veracity estimates for false tweets, increases the weight put on veracity in the sharing function, and increases the cost of sharing. The structural model is used to guarantee external validity and to evaluate alternative policies.
Bio | Emeric Henry is a microeconomist, using theory, experimental and empirical methods to study questions in law and economics. His research interest include economics of innovation and political economy. In 2009 he was awarded the "Chaire d'Excellence Junior" by the French National Research Agency - the Agence Nationale de la recherche (ANR) and the "Deutsche Bahn Prize" for outstanding research in organization and management. He was also a Fullbright and Schultz Scholar. In 2021 he was awarded an ANR and a McCourt Grant. Prior to joining Sciences Po, Emeric HENRY was an Assistant Professor at the London Business School. Emeric HENRY received his PhD in Economics from Stanford University after completion of his Master's Degree in Management Science and Engineering.