JOURNAL ARTICLE

"I found these places to be toxic": A mixed methods content analysis of visitors' impressions of incel forums.

  • Published In: Canadian Journal of Human Sexuality, 2024, v. 33, n. 2. P. 264 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Laplante, Sabrina; Labranche, Andrée-Ann; Boislard, Marie-Aude 3 of 3

Abstract

This article examines the varied impressions of visitors to involuntary celibate (incel) forums, which are online communities primarily composed of self-identified cisgender heterosexual men who experience involuntary celibacy and often express misogynistic views. Using a mixed-methods approach with 390 adults who had visited incel forums, the study identified six main categories of impressions ranging on a continuum from perceiving the forums as a threat to viewing them as a shelter. Women, individuals of other genders, and non-incels were more likely to perceive the forums as threatening, while men and self-identified incels tended to see them as a refuge. The findings highlight the heterogeneity of perceptions toward incel forums, revealing both recognition of the forums' toxic and aggressive content and empathy toward the distress and social difficulties experienced by their members. These nuanced insights may inform future research and professional practices aimed at understanding and addressing the needs of individuals involved with or affected by incel communities.

Additional Information

  • Source:Canadian Journal of Human Sexuality. 2024/09, Vol. 33, Issue 2, p264
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2024
  • ISSN:1188-4517
  • DOI:10.3138/cjhs-2023-0050
  • Accession Number:180087212
  • Copyright Statement:Copyright of Canadian Journal of Human Sexuality is the property of University of Toronto Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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