Will the Crowd Game the Algorithm? Using Layperson Judgments to Combat Misinformation on Social Media by Downranking Distrusted Sources

Abstract

© 2020 Owner/Author. How can social media platforms fight the spread of misinformation? One possibility is to use newsfeed algorithms to downrank content from sources that users rate as untrustworthy. But will laypeople be handicapped by motivated reasoning or lack of expertise, and thus unable to identify misinformation sites? And will they "game" this crowdsourcing mechanism in order to promote content that aligns with their partisan agendas? We conducted a survey experiment in which =984 Americans indicated their trust in numerous news sites. To study the tendency of people to game the system, half of the participants were told their responses would inform social media ranking algorithms. Participants trusted mainstream sources much more than hyper-partisan or fake news sources, and their ratings were highly correlated with professional fact-checker judgments. Critically, informing participants that their responses would influence ranking algorithms did not diminish these results, despite the manipulation increasing the political polarization of trust ratings.