Data Science/Computational Social Science Seminar: David Rand
Reducing misinformation sharing at scale using digital accuracy prompt ads
Please RSVP. Lunch provided.
Abstract
Interventions to reduce misinformation sharing have been a major focus in recent years. Developing “content-neutral” interventions that do not require specific fact-checks or warnings related to individual false claims is particularly important in developing scalable solutions. Here, we provide the first evaluations of a content-neutral intervention to reduce misinformation sharing conducted at scale in the field. Specifically, across two on-platform randomized controlled trials, one on Meta’s Facebook (N=33,043,471) and the other on Twitter (N=75,763), we find that simple messages reminding people to think about accuracy—delivered to large numbers of users using digital advertisements—reduce misinformation sharing, with effect sizes on par with what is typically observed in digital advertising experiments. On Facebook, in the hour after receiving an accuracy prompt ad, we found a 2.6% reduction in the probability of being a misinformation sharer among users who had shared misinformation the week prior to the experiment. On Twitter, over more than a week of receiving 3 accuracy prompt ads per day, we similarly found a 3.7% to 6.3% decrease in the probability of sharing low-quality content among active users who shared misinformation pre-treatment. These findings suggest that content-neutral interventions that prompt users to consider accuracy have the potential to complement existing content-specific interventions in reducing the spread of misinformation online.
Speaker bio
David Rand is the Erwin H. Schell Professor and professor of management science and brain and cognitive sciences at MIT. Bridging the fields of cognitive science, behavioral economics, and social psychology, Rand’s research combines behavioral experiments and online/field studies with mathematical/computational models to understand human decision-making. His work focuses on illuminating why people believe and share misinformation and “fake news”; understanding political psychology and polarization; and promoting human cooperation. He has published over 200 articles in peer-reviewed journals such Nature, Science, PNAS, the American Economic Review, Psychological Science, Management Science, New England Journal of Medicine and the American Journal of Political Science, and his work has received widespread media attention. Rand regularly advises technology companies such as Google, Meta/Facebook and TikTok in their efforts to combat misinformation, and has provided testimony about misinformation to the US and UK governments. He has also written for popular press outlets including the New York Times, Wired and New Scientist. He was named to Wired magazine’s Smart List 2012 of “50 people who will change the world,” chosen as a 2012 Pop!Tech Science Fellow, awarded the 2015 Arthur Greer Memorial Prize for Outstanding Scholarly Research, chosen as fact-checking researcher of the year in 2017 by the Poyner Institute’s International Fact-Checking Network, awarded the 2020 FABBS Early Career Impact Award from the Society for Judgment and Decision Making, and selected as a 2021 Best 40-Under-40 Business School Professor by Poets & Quants. Papers he has coauthored have been awarded Best Paper of the Year in Experimental Economics, Social Cognition, and Political Methodology.
About the DS/CSS seminar series
The University of Michigan School of Information’s Data Science/Computational Social Science seminar series brings together a vibrant and diverse community of scholars whose cutting-edge research in information science, computer science and the social sciences aims to broaden our understanding of important social and technological issues.
Organizers for the winter 2024 series are UMSI assistant professors Paramveer Dhillon and Sabina Tomkins.