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Out-group animosity drives engagement on social media
There has been growing concern about the role social media plays in political polarization. We investigated whether out-group animosity was particularly successful at generating engagement on two of the largest social media platforms: Facebook and Twitter. Analyzing posts from news media accounts an...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8256037/ https://www.ncbi.nlm.nih.gov/pubmed/34162706 http://dx.doi.org/10.1073/pnas.2024292118 |
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author | Rathje, Steve Van Bavel, Jay J. van der Linden, Sander |
author_facet | Rathje, Steve Van Bavel, Jay J. van der Linden, Sander |
author_sort | Rathje, Steve |
collection | PubMed |
description | There has been growing concern about the role social media plays in political polarization. We investigated whether out-group animosity was particularly successful at generating engagement on two of the largest social media platforms: Facebook and Twitter. Analyzing posts from news media accounts and US congressional members (n = 2,730,215), we found that posts about the political out-group were shared or retweeted about twice as often as posts about the in-group. Each individual term referring to the political out-group increased the odds of a social media post being shared by 67%. Out-group language consistently emerged as the strongest predictor of shares and retweets: the average effect size of out-group language was about 4.8 times as strong as that of negative affect language and about 6.7 times as strong as that of moral-emotional language—both established predictors of social media engagement. Language about the out-group was a very strong predictor of “angry” reactions (the most popular reactions across all datasets), and language about the in-group was a strong predictor of “love” reactions, reflecting in-group favoritism and out-group derogation. This out-group effect was not moderated by political orientation or social media platform, but stronger effects were found among political leaders than among news media accounts. In sum, out-group language is the strongest predictor of social media engagement across all relevant predictors measured, suggesting that social media may be creating perverse incentives for content expressing out-group animosity. |
format | Online Article Text |
id | pubmed-8256037 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-82560372021-07-16 Out-group animosity drives engagement on social media Rathje, Steve Van Bavel, Jay J. van der Linden, Sander Proc Natl Acad Sci U S A Social Sciences There has been growing concern about the role social media plays in political polarization. We investigated whether out-group animosity was particularly successful at generating engagement on two of the largest social media platforms: Facebook and Twitter. Analyzing posts from news media accounts and US congressional members (n = 2,730,215), we found that posts about the political out-group were shared or retweeted about twice as often as posts about the in-group. Each individual term referring to the political out-group increased the odds of a social media post being shared by 67%. Out-group language consistently emerged as the strongest predictor of shares and retweets: the average effect size of out-group language was about 4.8 times as strong as that of negative affect language and about 6.7 times as strong as that of moral-emotional language—both established predictors of social media engagement. Language about the out-group was a very strong predictor of “angry” reactions (the most popular reactions across all datasets), and language about the in-group was a strong predictor of “love” reactions, reflecting in-group favoritism and out-group derogation. This out-group effect was not moderated by political orientation or social media platform, but stronger effects were found among political leaders than among news media accounts. In sum, out-group language is the strongest predictor of social media engagement across all relevant predictors measured, suggesting that social media may be creating perverse incentives for content expressing out-group animosity. National Academy of Sciences 2021-06-29 2021-06-23 /pmc/articles/PMC8256037/ /pubmed/34162706 http://dx.doi.org/10.1073/pnas.2024292118 Text en Copyright © 2021 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by/4.0/This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY) (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Social Sciences Rathje, Steve Van Bavel, Jay J. van der Linden, Sander Out-group animosity drives engagement on social media |
title | Out-group animosity drives engagement on social media |
title_full | Out-group animosity drives engagement on social media |
title_fullStr | Out-group animosity drives engagement on social media |
title_full_unstemmed | Out-group animosity drives engagement on social media |
title_short | Out-group animosity drives engagement on social media |
title_sort | out-group animosity drives engagement on social media |
topic | Social Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8256037/ https://www.ncbi.nlm.nih.gov/pubmed/34162706 http://dx.doi.org/10.1073/pnas.2024292118 |
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