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Title: "How over is it?" Understanding the Incel Community on YouTube
Authors: Papadamou, Kostantinos 
Zannettou, Savvas 
Blackburn, Jeremy 
De Cristofaro, Emiliano 
Stringhini, Gianluca 
Sirivianos, Michael 
Major Field of Science: Engineering and Technology
Field Category: Computer and Information Sciences
Keywords: Incels;Involuntary celibates;Manosphere;Misogyny;Reddit;Youtube recommendation algorithm
Issue Date: 20-Oct-2021
Source: Proceedings of the ACM on Human-Computer Interaction, 2021, vol. 5, no. CSCW2, articl. no. 412
Volume: 5
Issue: CSCW2
Project: EnhaNcing seCurity And privacy in the Social wEb: a user centered approach for the protection of minors 
Journal: Proceedings of the ACM on Human-Computer Interaction 
Abstract: YouTube is by far the largest host of user-generated video content worldwide. Alas, the platform has also come under fire for hosting inappropriate, toxic, and hateful content. One community that has often been linked to sharing and publishing hateful and misogynistic content are the Involuntary Celibates (Incels), a loosely defined movement ostensibly focusing on men's issues. In this paper, we set out to analyze the Incel community on YouTube by focusing on this community's evolution over the last decade and understanding whether YouTube's recommendation algorithm steers users towards Incel-related videos. We collect videos shared on Incel communities within Reddit and perform a data-driven characterization of the content posted on YouTube. Among other things, we find that the Incel community on YouTube is getting traction and that, during the last decade, the number of Incel-related videos and comments rose substantially. We also find that users have a 6.3% chance of being suggested an Incel-related video by YouTube's recommendation algorithm within five hops when starting from a non Incel-related video. Overall, our findings paint an alarming picture of online radicalization: not only Incel activity is increasing over time, but platforms may also play an active role in steering users towards such extreme content.
Description: To appear at the 24th ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2021).This project has received funding from the European Union’s Horizon 2020 Research and Innovation program under the Marie Skłdowska-Curie ENCASE project (GA No. 691025) and the CONCORDIA project (GA No. 830927), the US National Science Foundation (grants: 1942610, 2114407, 2114411, and 2046590), and the UK’s National Research Centre on Privacy, Harm Reduction, and Adversarial Influence Online (UKRI grant: EP/V011189/1).
ISSN: 2573-0142
DOI: 10.1145/3479556
Rights: © Owner/author(s).
Type: Article
Affiliation : Cyprus University of Technology 
Max Planck Institute 
Binghamton University 
University College London 
Alan Turing Institute 
Boston University 
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