Patterned Radicalization: User Behavior Analysis and Antisemitic Language in QAnon Subreddits

This study investigates how people in certain online communities engage with and adopt hateful rhetoric, specifically examining the escalation of antisemitic language in two deplatformed QAnon-related subreddits. Utilizing a lexicon of implicit and explicit antisemitic terms, the research analyzes over 1.26 million Reddit posts and comments. This study’s objective is to describe the process through which users become more deeply engaged with antisemitic content within hate-filled subcultures found online. Through the application of survival models, chi-square tests, and logistic regressions, the findings reveal that most users do not begin their engagement using antisemitic language and instead engage with antisemitic content before posting it on their own. Moreover, users who transition to posting antisemitic language typically commence with posts containing implicit terms, progressively transitioning from implicit to explicit hate speech. This escalation is particularly pronounced among users demonstrating higher levels of engagement and those interacting with influential community members, often referred to as hyper-posters. The results indicate increased involvement, exposure, and interaction with antisemitic language, especially with hyper-posters, significantly predict increased and more extreme antisemitic language. These findings illuminate the dynamic and socially contingent process through which users engage with and internalize antisemitic language within subcultural digital spaces. The study posits that language radicalization is a structured process shaped by both individual user behavior and the broader community’s social architecture.

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Published
2026-02-10
DOI
https://doi.org/10.3390/info17020179
Primary Topic
Hate Speech and Cyberbullying Detection
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article
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article

Patterned Radicalization: User Behavior Analysis and Antisemitic Language in QAnon Subreddits

Jeffrey Kopstein, Dana Beth Weinberg, Noah D. Cohen, Peter Antonaros et al.
Information
Hate Speech and Cyberbullying Detection
article

Patterned Radicalization: User Behavior Analysis and Antisemitic Language in QAnon Subreddits

Jeffrey Kopstein, Dana Beth Weinberg, Noah D. Cohen, Peter Antonaros, Meyer D. Levy
article en

Abstract

This study investigates how people in certain online communities engage with and adopt hateful rhetoric, specifically examining the escalation of antisemitic language in two deplatformed QAnon-related subreddits. Utilizing a lexicon of implicit and explicit antisemitic terms, the research analyzes over 1.26 million Reddit posts and comments. This study’s objective is to describe the process through which users become more deeply engaged with antisemitic content within hate-filled subcultures found online. Through the application of survival models, chi-square tests, and logistic regressions, the findings reveal that most users do not begin their engagement using antisemitic language and instead engage with antisemitic content before posting it on their own. Moreover, users who transition to posting antisemitic language typically commence with posts containing implicit terms, progressively transitioning from implicit to explicit hate speech. This escalation is particularly pronounced among users demonstrating higher levels of engagement and those interacting with influential community members, often referred to as hyper-posters. The results indicate increased involvement, exposure, and interaction with antisemitic language, especially with hyper-posters, significantly predict increased and more extreme antisemitic language. These findings illuminate the dynamic and socially contingent process through which users engage with and internalize antisemitic language within subcultural digital spaces. The study posits that language radicalization is a structured process shaped by both individual user behavior and the broader community’s social architecture.

InformationVol. 17(2)
Queens College, CUNY (US), University of California, Irvine (US), Irvine University (US), Columbia University (US), John Jay College of Criminal Justice (US)
Reduced inequalities
Openalex Percentile: Top 62%
Hate Speech and Cyberbullying Detection
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