Abstract
Violent ideologies flourish in online communities that sanction extremist content. Communication in such communities includes a variety of modalities, such as text, memes, videos, and podcasts, which collectively radicalise their consumers. In this position paper, we argue that radicalisation is a nascent area for which machine learning and NLP are particularly apt. On the one hand, these technologies could mitigate the harms of human review of extremist content and stand to validate theories of radicalisation. On the other, such communities present an avenue for addressing key challenges in machine learning and NLP technologies, such as temporal distribution shifts and multi-modal alignment.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 9th Workshop on Online Abuse and Harms |
| Editors | Agostina Calabrese, Christine de Kock, Debora Nozza, Flor Miriam Plaza-del-Arco, Zeerak Talat, Francielle Vargas |
| Place of Publication | Kerrville, TX, USA |
| Publisher | Association for Computational Linguistics |
| Pages | 276-283 |
| Number of pages | 8 |
| ISBN (Print) | 9798891761056 |
| Publication status | Published - 1 Aug 2025 |
| Event | The 9th Workshop on Online Abuse and Harms - Austria Center Vienna, Vienna, Austria Duration: 31 Jul 2025 → 1 Aug 2025 Conference number: 9 https://www.workshopononlineabuse.com/ |
Workshop
| Workshop | The 9th Workshop on Online Abuse and Harms |
|---|---|
| Abbreviated title | WOAH 2025 |
| Country/Territory | Austria |
| City | Vienna |
| Period | 31/07/25 → 1/08/25 |
| Internet address |