Investigating Bots and Coordinated Influence Campaigns in Twitter Discussions of the 2019-20 Iran Protests
Bibliographic Data
| ID | 22008705 |
|---|---|
| Authors | Ehsan Dehghan (0000-0003-3139-5298, Queensland University of Technology), Brenda Moon (0000-0003-2571-0650, Queensland University of Technology), Tobias R Keller (0000-0001-5263-4812, Queensland University of Technology), Tobias Keller, Tiffany Graham (0000-0002-4053-9313, Queensland University of Technology), Timothy Graham, Axel Bruns (0000-0002-3943-133X, Queensland University of Technology), Daniel Angus (0000-0002-1412-5096, Queensland University of Technology) |
| Year | 2020 |
| Publication date | 2020-10-05 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | AoIR Selected Papers of Internet Research (JOURNAL) |
| Journal identifiers | ISSN: 2162-3317 • E-ISSN: 2162-3317 |
| Publisher | University of Illinois Libraries (PUBLISHER) |
| DOI | 10.5210/spir.v2020i0.11199 |
| OpenAlex | W3091992411 |
| Language | EN |
| Citations received | 1 |
| References cited | 7 |
Twitter has been a vital platform for organizing, coordinating, and amplifying voices during protests, especially in non-democratic countries. Although it is a globally used platform for protest movements, many studies focus on English-speaking and democratic countries. We overcome this research gap by investigating Persian, English, and Arabic tweets during the 2019-2020 protests in Iran. In this work-in-progress paper, we collected approximately 5,500,000 tweets, and apply social network analysis, Botometer and qualitative analysis, to map the Twittersphere revolving around Iran protests (RQ1). We focus on the evidence of the presence of bots, bot networks, coordinated misinformation campaigns and political astroturfing in the discussions (RQ2). Our preliminary results indicate the presence of strong homophilous networks of users formed around various political interests. At least two of the clusters in the network show an unusually high proportion of suspicious accounts. Interestingly, these clusters reflect antagonistic political affiliations—one consists mainly of pro-regime Iranian accounts, the other of anti-regime accounts tweeting in Arabic. The broader findings from this study will be valuable for understanding digital activism, protests, and political communication in authoritarian and semi-authoritarian contexts
Arabic · Authoritarianism · Contentious politics · Democracy · Disinformation · Focus group · Linguistics · Media studies · Misinformation · Persian · Political science · Politics · Public relations · Social media · Social movement · Social network analysis · Sociology · Hate Speech and Cyberbullying Detection · Law · Misinformation and Its Impacts · Social Media and Politics
| Unique citing works | 1 |
|---|---|
| Citations per year | 0,33 |
| Citation span | 2023 - 2023 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 1 |