TY - JOUR
T1 - How do social media feed algorithms affect attitudes and behavior in an election campaign?
AU - Guess, Andrew M.
AU - Malhotra, Neil
AU - Pan, Jennifer
AU - Barberá, Pablo
AU - Allcott, Hunt
AU - Brown, Taylor
AU - Crespo-Tenorio, Adriana
AU - Dimmery, Drew
AU - Freelon, Deen
AU - Gentzkow, Matthew
AU - González-Bailón, Sandra
AU - Kennedy, Edward
AU - Kim, Young Mie
AU - Lazer, David
AU - Moehler, Devra
AU - Nyhan, Brendan
AU - Rivera, Carlos Velasco
AU - Settle, Jaime
AU - Thomas, Daniel Robert
AU - Thorson, Emily
AU - Tromble, Rebekah
AU - Wilkins, Arjun
AU - Wojcieszak, Magdalena
AU - Xiong, Beixian
AU - De Jonge, Chad Kiewiet
AU - Franco, Annie
AU - Mason, Winter
AU - Stroud, Natalie Jomini
AU - Tucker, Joshua A.
N1 - Funding Information:
The costs associated with the research (such as participant fees, recruitment, and data collection) were paid by Meta. Ancillary support (for example, research assistants and course buyouts), as applicable, was sourced by academics from the Democracy Fund, the Hopewell Fund, the Guggenheim Foundation, the John S. and James L. Knight Foundation, the Charles Koch Foundation, the Hewlett Foundation, the Alfred P. Sloan Foundation, the University of Texas at Austin, New York University, Stanford University, the Stanford Institute for Economic Policy Research, and the University of Wisconsin-Madison.
Publisher Copyright:
© 2023 The Authors.
PY - 2023/7/28
Y1 - 2023/7/28
N2 - 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.
AB - 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.
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UR - http://www.scopus.com/inward/citedby.url?scp=85165822483&partnerID=8YFLogxK
U2 - 10.1126/science.abp9364
DO - 10.1126/science.abp9364
M3 - Article
C2 - 37498999
AN - SCOPUS:85165822483
SN - 0036-8075
VL - 381
SP - 398
EP - 404
JO - Science
JF - Science
IS - 6656
ER -