Russian Troll Social Media Attacks on Presidential Candidates during the 2016 U.S. Election: The Role of Frontrunner Status, Political Party, and Candidate Gender
Publisher
University of Southern CaliforniaCitation
Terán, L., Gahler, H., Montez, D., Kenski, K., & Rains, S. A. (2023). Russian Troll Social Media Attacks on Presidential Candidates during the 2016 US Election: The Role of Frontrunner Status, Political Party, and Candidate Gender. International Journal of Communication, 17, 22.Rights
Copyright © 2023 (Larissa Terán, Heather Gahler, Daniel Montez, Kate Kenski, and Stephen A. Rains). Licensed under the Creative Commons Attribution Non-commercial No Derivatives (by-nc-nd).Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
This study examines how the Russian Internet Research Agency (IRA) troll attacks against the 2016 U.S. presidential candidates on social media varied based on three important characteristics: frontrunner status, political party affiliation, and the gender of the candidate. The frequency of attacks, types of attacks, and audience engagement via retweets were assessed. A content analysis of 4,518 IRA troll messages posted on Twitter (i.e., tweets) shows that frontrunners, Democrats, and the female candidate received the most attacks. In terms of attack types, attacks on character/integrity occurred most frequently and were more likely to be directed at frontrunners, Democrats, and the female candidate. Tweets attacking these three groups were also more likely to be retweeted than tweets without an attack. © (2023) (Larissa Terán, Heather Gahler, Daniel Montez, Kate Kenski, and Stephen A. Rains). Licensed under the Creative Commons Attribution Non-commercial No Derivatives (by-nc-nd). Available at http://ijoc.org.Note
Open access journalISSN
1932-8036Version
Final Published VersionCollections
Except where otherwise noted, this item's license is described as Copyright © 2023 (Larissa Terán, Heather Gahler, Daniel Montez, Kate Kenski, and Stephen A. Rains). Licensed under the Creative Commons Attribution Non-commercial No Derivatives (by-nc-nd).