Shifting attention to accuracy can reduce misinformation online
David Rand
July 28, 2021, 4:40–5:15 PM
Abstract
In recent years, there has been a great deal of concern about the proliferation of false and misleading news on social media. Academics and practitioners alike have asked why people share such misinformation, and sought solutions to reduce the sharing of misinformation. I will discuss work that attempts to address both of these questions. First, we find that the veracity of headlines has little effect on sharing intentions, despite having a large effect on judgments of accuracy. This dissociation suggests that sharing does not necessarily indicate belief. Nonetheless, most participants say it is important to share only accurate news. To shed light on this apparent contradiction, we carried out survey experiments and a field experiment on Twitter; the results show that subtly shifting attention to accuracy increases the quality of news that people subsequently share. Together with additional computational analyses, these findings indicate that people often share misinformation because their attention is focused on factors other than accuracy—and therefore they fail to implement a strongly held preference for accurate sharing. Furthermore, we replicate these results in a large cross-cultural experiment with over 32,000 subjects from 16 countries on 6 continents. Our results challenge the popular claim that people value partisanship over accuracy, and provide evidence for scalable attention-based interventions that social media platforms could easily implement to counter misinformation online. For a preview, see https://twitter.com/DG_Rand/status/1372217700626411527?s=20 and https://www.nature.com/articles/s41586-021-03344-2
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, David’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. His work has been published 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 has received widespread media attention. 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.