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
Citations
Cites
Convolutional Neural Networks for Sentence Classification
Kim, Y. (2014) · Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.3115/v1/d14-1181 · Cited by 14,831
The online disinhibition effect
Suler, J. (2004) · CyberPsychology & Behavior · doi:10.1089/1094931041291295 · Cited by 4,375
Sentiment Analysis and Opinion Mining
Liu, B. (2012) · Synthesis lectures on human language technologies · doi:10.2200/s00416ed1v01y201204hlt016 · Cited by 3,995
Sentiment Analysis and Opinion Mining
Zhang, L., & Liu, B. (2017) · Springer eBooks · doi:10.1007/978-1-4899-7687-1_907 · Cited by 3,307
Linguistic Inquiry and Word Count (LIWC)
Chung, C. K., & Pennebaker, J. W. (2012) · IGI Global eBooks · doi:10.4018/978-1-60960-741-8.ch012 · Cited by 2,215
Document clustering based on non-negative matrix factorization
Xu, W., Liu, X., & Gong, Y. (2003) · doi:10.1145/860435.860485 · Cited by 1,889
Discriminative training methods for hidden Markov models
Collins, M. (2002) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.3115/1118693.1118694 · Cited by 1,881
A Survey on Hate Speech Detection using Natural Language Processing
Schmidt, A., & Wiegand, M. (2017) · SocialNLP@EACL · doi:10.18653/v1/w17-1101 · Cited by 1,478
Alphas, Betas, and Incels: Theorizing the Masculinities of the Manosphere
Ging, D. (2019) · Men and Masculinities · doi:10.1177/1097184x17706401 · Cited by 1,245
Colleoni, E., Rozza, A., & Arvidsson, A. (2014) · Journal of Communication · doi:10.1111/jcom.12084 · Cited by 1,151
Research works printed but not linked: 8
- Brown, 2016, Defusing Hate: A Strategic Communication Guide to Counteract Dangerous Speech
- Chollet, 2015, Keras: Deep Learning Library for Theano and Tensorflow
- Douglas, 2009, Psychology, Discrimination and Hate Groups Online, 155
- Haythornthwaite, 2009, Social Networks and Online Community, 121
- Kämper, 2011, [r]echte Kerle. Zur Kumpanei der MännerRECHTSbewegung
- Nockleby, 2000, Hate Speech, 1277
- 10.15655/mw/2018/v9i3/49480 · DOI
- Zimmerman, 2018, Recognizing the Violent Extremist Ideology of ‘Incels’, 1
Cited by
Sorted by citations
Sluts and soyboys: MGTOW and the production of misogynistic online harassment
Jones, C. D., Trott, V. A., & Wright, S. (2019) · New Media & Society · doi:10.1177/1461444819887141 · Cited by 206
Chang, W. (2022) · Feminist Media Studies · doi:10.1080/14680777.2020.1804976 · Cited by 142
Educational Research and Innovation
OECD, & Centre for Educational Research and Innovation (2009) · Educational research and innovation · doi:10.1787/20769679 · Cited by 129
“Victims of feminism”: exploring networked misogyny and #MeToo in the manosphere
Dickel, V., & Evolvi, G. (2023) · Feminist Media Studies · doi:10.1080/14680777.2022.2029925 · Cited by 122
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
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