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Cited by 111Social Media and PoliticsMisinformation and Its ImpactsHate Speech and Cyberbullying Detection

Mobilizing the Trump Train: Understanding Collective Action in a Political Trolling Community

Open access
Flores-Saviaga, Claudia, Keegan, Brian, Savage, Saiph·2018·Proceedings of the International AAAI Conference on Web and Social Media
DOI 10.1609/icwsm.v12i1.15024
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Abstract

Political trolls initiate online discord not only for the lulz (laughs), but also for ideological reasons, such as promoting their desired political candidates. Political troll groups recently gained spotlight because they were considered central in helping Donald Trump win the 2016 US presidential election, which involved difficult mass mobilizations. Political trolls face unique challenges as they must build their own communities while simultaneously disrupting others. However, little is known about how political trolls mobilize sufficient participation to suddenly become problems for others. We performed a quantitative longitudinal analysis of more than 16 million comments from one of the most popular and disruptive political trolling communities, the subreddit /r/The Donald (T_D). We use T_D as a lens to understand participation and collective action within these deviant spaces. In specific, we first study the characteristics of the most active participants to uncover what might drive their sustained participation. Next, we investigate how these active individuals mobilize their community to action. Through our analysis we uncover that the most active employed distinct discursive strategies to mobilize participation, and deployed technical tools like bots to create a shared identity and sustain engagement. We conclude by providing data-backed design implications for designers of civic media.

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  • Participation in r/The_Donald is a valid proxy to study Donald Trump support.

    “Participation in this subreddit is a valid proxy to study Donald Trump support, as the rules of this subreddit explicitly state that the community is for “Trump Supporters Only”, and that dissenting users will be removed.”

    From No echo in the chambers of political interactions on Reddit (2021) · cites this paper as [34]

    The Introduction describes r/The_Donald as a community whose members circulated pro-Trump material, supporting its relevance to studying Trump supporters. But the Limitations and Future Work section says the authors do not know much about participants’ identities and motivations. Our copy does not establish that participation is a valid proxy for Trump support or state the claimed rules about supporters and removal of dissenters. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

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Cites

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Research works printed but not linked: 23

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Cited by

Sorted by citations

Authors
Flores-Saviaga, C., Keegan, B., & Savage, S.
Affiliations
  • West Virginia University (US)
  • University of Colorado Boulder (US)
ORCID
Venue
Proceedings of the International AAAI Conference on Web and Social Media
Publisher
Association for the Advancement of Artificial Intelligence (AAAI)
Published
2018-06-15
Volume
12
Issue
1
ISSN
  • 2162-3449 (ISSN-L)
  • 2334-0770
DOI
10.1609/icwsm.v12i1.15024
OpenAlex
W2807371872
Cited by
111
References
3
Citations by year
2025: 4 · 2024: 3 · 2023: 9 · 2022: 21 · 2021: 31 · 2020: 21 · 2019: 15 · 2018: 7
FWCI
71.42
Type
conference paper
Language
en
Open access
Locations
  • Proceedings of the International AAAI Conference on Web and Social Media (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI)) (submittedVersion)
  • arXiv (Cornell University)
Topics
  • Social Sciences › Communication › Social Media and Politics
  • Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
  • Physical Sciences › Computer Science › Artificial Intelligence › Hate Speech and Cyberbullying Detection
Keywords
collective action, online communities, 2016 US presidential election, Donald Trump, political mobilization, bots, shared identity, discursive strategies

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