Abstract
This study examines interaction patterns on the web forum Incels.net through Social Network Analysis, focusing on the formation of echo chambers characterized by toxic language. We explore several hypotheses: (H2) users tend to engage in animated one-to-one interactions by quoting each other; (H4) frequent posters are less likely to be quoted by less active users, indicating a lack of clear leadership; and (H5) users sharing the same sentiment are more likely to participate in large discussions (echo chambers) but do not engage in one-to-one conversations. Our findings enhance the understanding of behaviors that may contribute to radicalization within fringe online communities and offer insights for future research into similar extreme hate forums.
| Original language | English |
|---|---|
| Title of host publication | 2024 IEEE International Conference on Big Data, BigData 2024 |
| Editors | Wei Ding, Chang-Tien Lu, Fusheng Wang, Liping Di, Kesheng Wu, Jun Huan, Raghu Nambiar, Jundong Li, Filip Ilievski, Ricardo Baeza-Yates, Xiaohua Hu |
| Publisher | Institute of Electrical and Electronics Engineers |
| Pages | 6269-6278 |
| Number of pages | 10 |
| ISBN (Electronic) | 979-8-3503-6248-0 |
| DOIs | |
| Publication status | Published - 16 Jan 2025 |
| Externally published | Yes |
| Event | 2024 IEEE International Conference on Big Data, BigData 2024 - Washington, United States Duration: 15 Dec 2024 → 18 Dec 2024 |
Conference
| Conference | 2024 IEEE International Conference on Big Data, BigData 2024 |
|---|---|
| Country/Territory | United States |
| City | Washington |
| Period | 15/12/24 → 18/12/24 |
Funding
This work was partially supported by project SERICS (PE00000014) under the MUR National Recovery and Resilience Plan funded by the European Union - NextGenerationEU.
Keywords
- Leadership
- Social networking (online)
- Focusing
- Oral communication
- Network analyzers
- language-based echo chambers
- Social Networks
- TERGMs
- Inceldom
- Sentiment Analysis
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