Published in Science, the office journal of the American Association for the Advancement of Science, July 2023

LEAD AUTHORS
Sandra González-Bailón, Annenberg School for Communication, University of Pennsylvania
David Lazer, Network Science Institute, Northeastern University
PabloBarberá, Meta
Meiqing Zhang, Meta
Including The Integrity Project's Young Mie Kim of the School of Journalism and Mass Communication at the University of Wisconsin–Madison, along with 21 other contributors

ABSTRACT
Does Facebook enable ideological segregation in political news consumption? We analyzed exposure to news during the U.S. 2020 election using aggregated data for 208 million U.S. Facebook users. We compared the inventory of all political news that users could have seen in their feeds with the information that they saw (after algorithmic curation) and the information with which they engaged. We show that ideological segregation is high and increases as we shift from potential exposure to actual exposure to engagement; there is an asymmetry between conservative and liberal audiences, with a substantial corner of the news ecosystem consumed exclusively by conservatives; and most misinformation, as identified by Meta’s Third-Party Fact-Checking Program, exists within this homogeneously conservative corner, which has no equivalent on the liberal side. Sources favored by conservative audiences were more prevalent on Facebook’s news ecosystem than those favored by liberals.

Social media platforms have a large and growing role in shaping access to information, including information about politics. However, few studies systematically map this part of the information ecosystem, with minimal examination of within-platform attention and information consumption. There is virtually no research comparing what people could potentially see within platforms and what they actually see. In this work, we address these questions with data on users’ access and engagement to political news on Facebook during the U.S. 2020 election. MORE

Photo by Ketut Subiyanto