Exploring incel group dynamics: a computational study of hierarchy and group-boundary policing

Veronika Solopova (), Mihaela Popa-Wyatt () and Justina Berškytė ()
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Veronika Solopova: Technische Universität Berlin
Mihaela Popa-Wyatt: University of Manchester
Justina Berškytė: University of Manchester

Journal of Computational Social Science, 2025, vol. 8, issue 2, No 1, 25 pages

Abstract: Abstract Incels (involuntary celibates) are part of a broader misogynistic culture known as the manosphere. Some communities within the manosphere, including incels, promote gender-based violence through misogynistic rhetoric and ideology. Incels are men who struggle to form romantic relationships and thus seek solace in online forums to find a sense of purpose and community. The community is organised around an ideology and a hierarchical classification of members. This paper presents a computational linguistic analysis of the utterances made within the community. We analyse the linguistic patterns of six different ranks of users: paragons, high-rank users, low-rank users, greycels, banned users, and self-banned/deleted users. We conducted an analysis of the sentiments expressed between ranks and of the affective attitude of posters when discussing a variety of topics. We then we analysed linguistic features, also conditioned on the rank of the poster. These analyses reveal qualitative differences between users of different ranks in how they express themselves and their sentiments. Finally, we trained models based on the linguistic features of users’ posts and show that already based on this information it is possible to predict the rank of users. Overall, our results indicate that the incel community has developed distinctive linguistic patterns to disseminate their ideology and that these linguistic patterns vary according to the rank of an incel within the community. This methodology offers a robust framework for studying similar echo chamber-like communities.

Keywords: Incels; Hierarchy; Status; Group-boundary policing; Inter-rank dynamics and emotional patterns; Sentiment analysis; Machine learning classification (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s42001-024-00357-5

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