The DOI matches its Crossref record; 51 of the 53 references it cites were found in a registry or an index.
Online hatred of women in the Incels.me forum: Linguistic analysis and automatic detection
Abstract
This paper presents a study of the (now suspended) online discussion forum Incels.me and its users, involuntary celibates or incels , a virtual community of isolated men without a sexual life, who see women as the cause of their problems and often use the forum for misogynistic hate speech and other forms of incitement. Involuntary celibates have attracted media attention and concern, after a killing spree in April 2018 in Toronto, Canada. The aim of this study is to shed light on the group dynamics of the incel community, by applying mixed-methods quantitative and qualitative approaches to analyze how the users of the forum create in-group identity and how they construct major out-groups, particularly women. We investigate the vernacular used by incels, apply automatic profiling techniques to determine who they are, discuss the hate speech posted in the forum, and propose a Deep Learning system that is able to detect instances of misogyny, homophobia, and racism, with approximately 95% accuracy.
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In the citing paper
“In response to the rise of the feminist movement, several misogynist and anti-feminist groups have emerged (Jaki et al., 2019; Marwick & Caplan, 2018).”
From Technology-Facilitated Gender-Based Violence, Hate Speech, and Terrorism: A Risk Assessment on the Rise of the Incel Rebellion in Canada (2023) · cites this paper as Jaki et al., 2019
In the citing paper
“As a result, one of the incel subculture's primary goals is that masculine hegemony be re-established (Jaki et al., 2019; O’Malley et al., 2020).”
From Technology-Facilitated Gender-Based Violence, Hate Speech, and Terrorism: A Risk Assessment on the Rise of the Incel Rebellion in Canada (2023) · cites this paper as Jaki et al., 2019
In the citing paper
“Incels combine an entitlement to sex with self-deprecation and perceptions of victimization by women (Bratich & Banet-Weiser, 2019; Jaki et al., 2019).”
From Technology-Facilitated Gender-Based Violence, Hate Speech, and Terrorism: A Risk Assessment on the Rise of the Incel Rebellion in Canada (2023) · cites this paper as Jaki et al., 2019
In the citing paper
“The movement moved online during 1980–1990s, creating an online network, or manosphere, that sought to reinstate masculine hegemony (Jaki et al., 2019).”
From Technology-Facilitated Gender-Based Violence, Hate Speech, and Terrorism: A Risk Assessment on the Rise of the Incel Rebellion in Canada (2023) · cites this paper as Jaki et al., 2019
In the citing paper
“Incels are 'involuntary celibates,' men who blame women for being rejected, as was the aforementioned case of Rodger (Sylvia Jaki, et al. 2019).”
From “Victims of feminism”: exploring networked misogyny and #MeToo in the manosphere (2023) · cites this paper as Sylvia Jaki, et al. 2019
In the citing paper
“and emboldens individuals to act in violence (Jaki et al., 2019).”
From Technology-Facilitated Gender-Based Violence, Hate Speech, and Terrorism: A Risk Assessment on the Rise of the Incel Rebellion in Canada (2023) · cites this paper as Jaki et al., 2019
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Metadata
- Authors
- Jaki, S., De Smedt, T., Gwóźdź, M., Panchal, R., Rossa, A., & De Pauw, G.
- Affiliations
- University of Hildesheim (DE)
- University of Antwerp
- Ludwig-Maximilians-Universität München (DE)
- Columbia University (US)
- University of Hull (GB)
- Textgain
- Venue
- Journal of Language Aggression and Conflict
- Publisher
- John Benjamins Publishing Company
- Published
- 2019-07-08
- Volume
- 7
- Issue
- 2
- Pages
- 240-268
- ISSN
- 2213-1272 (ISSN-L)
- 2213-1280
- OpenAlex
- W2959053582
- Cited by
- 226
- References
- 53
- Citations by year
- 2026: 32 · 2025: 41 · 2024: 30 · 2023: 29 · 2022: 36 · 2021: 29 · 2020: 24 · 2019: 3
- FWCI
- 10.49
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Language Aggression and Conflict (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Hate Speech and Cyberbullying Detection
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
- Keywords
- online hate speech, misogyny, online forums, ingroup identification, outgroup, group dynamics, vernacular language, hate speech detection, homophobia, racism, deep learning
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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