How do social media feed algorithms affect attitudes and behavior in an election campaign?

Journal Article
Publication date: 
07/2023
Authors: 
Andrew Guess
Neil Malhotra
Jennifer Pan
Pablo Barberá
Hunt Allcott
Taylor Brown
Adriana Crespo-Tenorio
Drew Dimmery
Deen Freelon
Matthew Gentzkow
Sandra Gonzalez-Bailon
Edward Kennedy
Young Mie Kim
David Lazer
Devra Moehler
Brendan Nyhan
Carlos Velasco Rivera
Jaime Settle
Daniel Robert Thomas
Emily A. Thorson
Rebekah Tromble
Arjun Wilkins
Magdalena Wojcieszak
Beixian Xiong
Chad Kiewiet De Jonge
Annie Franco
Winter Mason
Natalie Jomini Stroud
Joshua Tucker
How do social media feed algorithms affect attitudes and behavior in an election campaign?

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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