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. 2023 May 8;18(5):e0283971. doi: 10.1371/journal.pone.0283971. eCollection 2023.
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Affiliations 1 Operations and Information Management, Georgetown University, Washington, District of Columbia, United States of America. 2 Technology, Operations, and Statistics, New York University, New York, New York, United States of America. 3 Operations Research, Yale University, New Haven, Connecticut, United States of America.
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Michael Rossetti et al. PLoS One. 2023
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. 2023 May 8;18(5):e0283971. doi: 10.1371/journal.pone.0283971. eCollection 2023. Affiliations 1 Operations and Information Management, Georgetown University, Washington, District of Columbia, United States of America. 2 Technology, Operations, and Statistics, New York University, New York, New York, United States of America. 3 Operations Research, Yale University, New Haven, Connecticut, United States of America.
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Abstract
Automated social media accounts, known as bots, have been shown to spread disinformation and manipulate online discussions. We study the behavior of Twitter retweet bots during the first impeachment of US President Donald Trump. We collected over 67.7 million impeachment-related tweets from 3.6 million users, including their 53.6 million edge follower networks. We found that while bots represent 1% of all users, they account for more than 31% of all impeachment-related tweets. We also found that bots share more disinformation, but use less toxic language than other users. Among the supporters of the Qanon conspiracy theory, a popular disinformation campaign, bots have a prevalence close to 10%. The follower network of Qanon supporters exhibits a hierarchical structure, with bots acting as central hubs surrounded by isolated individuals. We measure the effect of the bot using a general measure of centrality of harmonic influence. We found that there was a greater number of pro-Trump bots, but on a per-bot basis, anti-Trump and pro-Trump bots had a similar impact, while Qanon bots had less impact. This lower effect is due to the homophily of the Qanon follower network, suggesting that this disinformation often spreads within online echo-chambers.
Copyright: 2023 Rossetti, Zaman. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Statement of conflict of interest
The authors declare that no competing interests exist.
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