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Assessing the Russian Internet Research Agency’s impact on the political attitudes and behaviors of American Twitter users in late 2017
Bail, Christopher A.; Guay, Brian; Maloney, Emily; u. a. (2020): Assessing the Russian Internet Research Agency’s impact on the political attitudes and behaviors of American Twitter users in late 2017, in: Proceedings of the National Academy of Sciences of the United States of America, Washington, DC: National Acad. of Sciences, Jg. 117, Nr. 1, S. 243–250, doi: 10.1073/pnas.1906420116.
Faculty/Chair:
Title of the Journal:
Proceedings of the National Academy of Sciences of the United States of America
ISSN:
0027-8424
1091-6490
Publisher Information:
Year of publication:
2020
Volume:
117
Issue:
1
Pages:
Language:
English
Abstract:
There is widespread concern that Russia and other countries have launched social-media campaigns designed to increase political divisions in the United States. Though a growing number of studies analyze the strategy of such campaigns, it is not yet known how these efforts shaped the political attitudes and behaviors of Americans. We study this question using longitudinal data that describe the attitudes and online behaviors of 1,239 Republican and Democratic Twitter users from late 2017 merged with nonpublic data about the Russian Internet Research Agency (IRA) from Twitter. Using Bayesian regression tree models, we find no evidence that interaction with IRA accounts substantially impacted 6 distinctive measures of political attitudes and behaviors over a 1-mo period. We also find that interaction with IRA accounts were most common among respondents with strong ideological homophily within their Twitter network, high interest in politics, and high frequency of Twitter usage. Together, these findings suggest that Russian trolls might have failed to sow discord because they mostly interacted with those who were already highly polarized. We conclude by discussing several important limitations of our study—especially our inability to determine whether IRA accounts influenced the 2016 presidential election—as well as its implications for future research on social media influence campaigns, political polarization, and computational social science.
GND Keywords: ; ; ;
Fehlinformation
Social Media
Polarisierung
Computational social science
Keywords: ; ; ;
misinformation
social media
political polarization
computational social science
DDC Classification:
RVK Classification:
Peer Reviewed:
Yes:
International Distribution:
Yes:
Open Access Journal:
Yes:
Type:
Article
Activation date:
August 13, 2024
Versioning
Question on publication
Permalink
https://fis.uni-bamberg.de/handle/uniba/97249