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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Publication Details

Journal
UNC Libraries
Published
2025-03-19
DOI
https://doi.org/10.17615/veqw-py41
Citations
10
Primary Topic
Social Media and Politics
Type
article
Field-Weighted Citation Impact
38.64

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article

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

Rebekah Tromble, Matthew Gentzkow, Annie Franco, Pablo Barberá et al.
10 citations
UNC Libraries
Social Media and Politics
38.64
article

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

Rebekah Tromble, Matthew Gentzkow, Annie Franco, Pablo Barberá, Brendan Nyhan, David Lazer, Taylor Brown, Devra Moehler, Emily Thorson, Adriana Crespo-Tenorio, Jaime E. Settle, Neil Malhotra, Daniel Robert Thomas, Arjun Wilkins, Chad Kiewiet de Jonge, Young Mie Kim, Magdalena Wojcieszak, Andrew M. Guess, Edward H. Kennedy, Drew Dimmery, Sandra González‐Bailón, Natalie Jomini Stroud, Hunt Allcott, Joshua A. Tucker, Carlos Velasco Rivera, Deen Freelon, Jennifer Pan, Winter Mason, B.S. Xiong
article en
10 citations

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.

UNC Libraries
University of North Carolina at Chapel Hill (US)
Alfred P. Sloan Foundation, John Simon Guggenheim Memorial Foundation, John S. and James L. Knight Foundation, University of Wisconsin-Madison, Charles Koch Foundation, York University, Nutrition Obesity Research Center, University of North Carolina, Stanford Institute for Economic Policy Research
Openalex Percentile: Top 0%
Social Media and Politics
38.64
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