Year: 2023
Type: article
Abstract: We investigated the effects of Facebook's and Instagram's feed algorithms during the 2020 US election. We assigned a sample of consenting users to reverse-chronologically-ordered feeds instead of the default algorithms. Moving users out of algorithmic feeds substantially decreased the time they spent on the platforms and their activity. The chronological feed also affected exposure to content: The amount of political and untrustworthy content they saw increased on both platforms, the amount of content classified as uncivil or containing slur words they saw decreased on Facebook, and the amount of content from moderate friends and sources with ideologically mixed audiences they saw increased on Facebook. Despite these substantial changes in users' on-platform experience, the chronological feed did not significantly alter levels of issue polarization, affective polarization, political knowledge, or other key attitudes during the 3-month study period.
Source: Science
Authors: Andrew M. Guess, Neil Malhotra, Jennifer Pan, Pablo Barberá, Hunt Allcott, Taylor Brown, Adriana Crespo-Tenorio, Drew Dimmery, Deen Freelon, Matthew Gentzkow, Sandra González-Bailón, Edward Kennedy, Young Mie Kim, David Lazer, Devra Moehler, Brendan Nyhan, Carlos Velasco Rivera, Jaime Settle, Daniel Robert Thomas, Emily Thorson, Rebekah Tromble, Arjun Wilkins, Magdalena Wojcieszak, Beixian Xiong, Chad Kiewiet de Jonge, Annie Franco, Winter Mason, Natalie Jomini Stroud, Joshua A. Tucker
Institutions: Princeton University, Stanford University, Meta (United States), University of Vienna, University of North Carolina at Chapel Hill, University of Pennsylvania, Carnegie Mellon University, University of Wisconsin–Madison, Northeastern University, Dartmouth College, William & Mary, Syracuse University, George Washington University, University of California, Davis, University of Amsterdam, Center for Media Engagement, The University of Texas at Austin, New York University
Language: English
Topic: Social Media and Politics
Subfield: Communication
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
Funders: Alfred P. Sloan Foundation, American Association for the Advancement of Science, William and Flora Hewlett Foundation, John Simon Guggenheim Memorial Foundation, John S. and James L. Knight Foundation, Google, University of Wisconsin-Madison, Charles Koch Foundation, York University, Nutrition Obesity Research Center, University of North Carolina, Stanford Institute for Economic Policy Research, National Opinion Research Center
OpenAlex ID: W4385298751