Webcast Option: https://yale.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=436c733e-1ffb-4220-abdb-b38a013b196c
Title:
Interrupting Misinformation with Community Notes
Abstract: Social networks scaffold the diffusion of information on social media. Much attention has been given to the spread of true vs. false content on online social platforms, including the structural differences between their diffusion patterns. However, much less is known about how platform interventions on false content alter the engagement with and diffusion of such content. In this work, we estimate the causal effects of Community Notes, a novel fact-checking feature adopted by X (formerly Twitter) to solicit and vet crowd-sourced fact-checking notes for false content. We gather detailed time series data for 40,074 posts for which notes have been proposed and use synthetic control methods to estimate a range of counterfactual outcomes. We find that attaching fact-checking notes significantly reduces the engagement with and diffusion of false content. We estimate that, on average, the notes resulted in reductions of 45.7% in reposts, 43.5% in likes, 22.9% in replies, and 14.0% in views after being attached. Over the posts’ entire lifespans, these reductions amount to 11.4% fewer reposts, 13.0% fewer likes, 7.3% fewer replies, and 5.7% fewer views on average. In reducing reposts, we observe that diffusion cascades for fact-checked content are less deep, but not less broad, than synthetic control estimates for non-fact-checked content with similar reach. Discussing joint work with Jonas Juul, Isaac Slaughter, Axel Peytevin, and Martin Saveski.
Bio: Johan Ugander is an Associate Professor at Yale University in the Department of Statistics & Data Science. His research develops algorithmic and statistical frameworks for analyzing social networks, social systems, and other large-scale social and behavioral data. Prior to joining the Yale faculty in 2025 he spent a decade as faculty at Stanford. He obtained his Ph.D. in Applied Mathematics from Cornell University in 2014 and was a postdoc at Microsoft Research 2014-15. His awards include a NSF CAREER Award, a Young Investigator Award from the Army Research Office (ARO), the 2025 Test of Time Award from the Web Science Trust, numerous Best Paper Awards, and the 2016 Eugene L. Grant Undergraduate Teaching Award from Stanford’s Department of Management Science & Engineering.
3:30pm - Pre-talk meet and greet teatime - 219 Prospect Street, 13 floor, there will be light snacks and beverages in the kitchen area. For more details and upcoming events visit our website at https://statistics.yale.edu/calendar.