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    <abstract>The paper investigates to what extent linguistic features, primarily emotional and affective signals, serve as a common denominator in the online texts of various extremist groups. Examining social media data from multiple sources, this research focuses on ideologies such as far-right, jihadist, and various manosphere subgroups. Key results demonstrate distinct emotional profiles across ideologies, with “disgust” emerging as a dominant emotion in many extremist discourses, while “joy” is most prominent in the analyzed religious extremist content. Statistically significant dissimilarities in emotional expression patterns were confirmed, allowing for differentiation between ideological groups. Classifiers, particularly the DeBERTa model, demonstrated a strong capability to reliably distinguish between extremist groups based solely on linguistic characteristics.</abstract>
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%0 Conference Proceedings
%T Cross-Ideological Hallmarks of Extremist Rhetoric in Social Media
%A Omarzae, Hasan
%A Gambäck, Björn
%Y Calabrese, Agostina
%Y Davidson, Thomas
%Y de Kock, Christine
%Y Khurana, Urja
%Y Marchiori Manerba, Marta
%Y Piot, Paloma
%Y Talat, Zeerak
%S Proceedings of the 10th Workshop on Online Abuse and Harms (WOAH)
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-487-3
%F omarzae-gamback-2026-cross
%X The paper investigates to what extent linguistic features, primarily emotional and affective signals, serve as a common denominator in the online texts of various extremist groups. Examining social media data from multiple sources, this research focuses on ideologies such as far-right, jihadist, and various manosphere subgroups. Key results demonstrate distinct emotional profiles across ideologies, with “disgust” emerging as a dominant emotion in many extremist discourses, while “joy” is most prominent in the analyzed religious extremist content. Statistically significant dissimilarities in emotional expression patterns were confirmed, allowing for differentiation between ideological groups. Classifiers, particularly the DeBERTa model, demonstrated a strong capability to reliably distinguish between extremist groups based solely on linguistic characteristics.
%U https://aclanthology.org/2026.woah-1.17/
%P 192-203

Markdown (Informal)

[Cross-Ideological Hallmarks of Extremist Rhetoric in Social Media](https://aclanthology.org/2026.woah-1.17/) (Omarzae & Gambäck, WOAH 2026)

• Cross-Ideological Hallmarks of Extremist Rhetoric in Social Media (Omarzae & Gambäck, WOAH 2026)

ACL

• Hasan Omarzae and Björn Gambäck. 2026. Cross-Ideological Hallmarks of Extremist Rhetoric in Social Media. In Proceedings of the 10th Workshop on Online Abuse and Harms (WOAH), pages 192–203, Budapest, Hungary. Association for Computational Linguistics.