Assessing the Extent and Types of Hate Speech in Fringe Communities: A Case Study of Alt-Right Communities on 8chan, 4chan, and Reddit
Open accessAbstract
Recent right-wing extremist terrorists were active in online fringe communities connected to the alt-right movement. Although these are commonly considered as distinctly hateful, racist, and misogynistic, the prevalence of hate speech in these communities has not been comprehensively investigated yet, particularly regarding more implicit and covert forms of hate. This study exploratively investigates the extent, nature, and clusters of different forms of hate speech in political fringe communities on Reddit, 4chan, and 8chan. To do so, a manual quantitative content analysis of user comments ( N = 6,000) was combined with an automated topic modeling approach. The findings of the study not only show that hate is prevalent in all three communities (24% of comments contained explicit or implicit hate speech), but also provide insights into common types of hate speech expression, targets, and differences between the studied communities.
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The findings are consistent with prior research showing that alternative social media and particularly fringe communities like 4Chan provide a welcoming environment for the spread of toxic content, likely due to their self-positioning as safe havens for such statements and their corresponding loose moderation rules.
“Thus, our findings are consistent with prior research showing that alternative social media and particularly fringe communities like 4Chan provide a welcoming environment for the spread of toxic content (Finkelstein et al., 2020; Rieger et al., 2021; Zannettou et al., 2018), likely due to their self-positioning as safe havens for such statements and their corresponding loose moderation rules (Fris”
From The Seed of Doubt: Examining the Role of Alternative Social and News Media for the Birth of a Conspiracy Theory (2024) · cites this paper as Rieger et al., 2021
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Extremist discourse on alt-right sub-reddit: An Inferential Network Analysis Approach
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Punishing or regulating? US media attention to hate crime and speech
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Platformed Mainstreaming: How and for What Does the Online Far Right Use Hyperlinks?
Keşkekci, D., & Sponholz, L. (2025) · Springer eBooks · doi:10.1007/978-3-031-85963-2_6
Theorizing networked counterpublics sanctions
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Pain in a Safe Space: Mapping Emotions and Discourse in the Womenintech Subreddit
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Reaching a larger audience: Content-related strategies of the far right on VK
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Rethinking Ground Truth: A Case Study on Human Label Variation in MLLM Benchmarking
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- Authors
- Rieger, D., Kümpel, A. S., Wich, M., Kiening, T., & Groh, G.
- Affiliations
- Ludwig-Maximilians-Universität München (DE)
- Technische Universität Dresden (DE)
- Technical University of Munich (DE)
- Venue
- Social Media + Society
- Publisher
- SAGE Publications
- Published
- 2021-10
- Volume
- 7
- Issue
- 4
- ISSN
- 2056-3051 (ISSN-L)
- OpenAlex
- W3209715443
- Cited by
- 102
- References
- 38
- Citations by year
- 2026: 16 · 2025: 24 · 2024: 23 · 2023: 25 · 2022: 14
- FWCI
- 5.54
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Social Media + Society (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Hate Speech and Cyberbullying Detection
- Social Sciences › Political Science and International Relations › Populism, Right-Wing Movements
- Social Sciences › Communication › Social Media and Politics
- Keywords
- hate speech, alt-right, 4chan, Reddit, right-wing extremism, implicit hate speech, online comments, topic modeling
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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