I am an assistant professor of politics and public affairs at Princeton University. I use a combination of experimental methods, large datasets, machine learning, and innovative measurement to study how people choose, process, spread, and respond to information about politics.
I’m a founding co-editor of the Journal of Quantitative Description: Digital Media, with Kevin Munger and Eszter Hargittai. You can read our essay introducing the journal’s philosophy and goals here.
As the primary arena for viral misinformation shifts toward transnational threats, the search continues for scalable countermeasures compatible with principles of transparency and free expression. We conducted a randomized field experiment evaluating the impact of source credibility labels embedded in users’ social feeds and search results pages. By combining representative surveys (n = 3337) and digital trace data (n = 968) from a subset of respondents, we provide a rare ecologically valid test of such an intervention on both attitudes and behavior. On average across the sample, we are unable to detect changes in real-world consumption of news from low-quality sources after 3 weeks. We can also rule out small effects on perceived accuracy of popular misinformation spread about the Black Lives Matter movement and coronavirus disease 2019. However, we present suggestive evidence of a substantively meaningful increase in news diet quality among the heaviest consumers of misinformation. We discuss the implications of our findings for scholars and practitioners.