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Toxic language based echo chambers on the Incels.net community: A network analysis approach

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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 languageEnglish
Title of host publication2024 IEEE International Conference on Big Data, BigData 2024
EditorsWei Ding, Chang-Tien Lu, Fusheng Wang, Liping Di, Kesheng Wu, Jun Huan, Raghu Nambiar, Jundong Li, Filip Ilievski, Ricardo Baeza-Yates, Xiaohua Hu
PublisherInstitute of Electrical and Electronics Engineers
Pages6269-6278
Number of pages10
ISBN (Electronic)979-8-3503-6248-0
DOIs
Publication statusPublished - 16 Jan 2025
Externally publishedYes
Event2024 IEEE International Conference on Big Data, BigData 2024 - Washington, United States
Duration: 15 Dec 202418 Dec 2024

Conference

Conference2024 IEEE International Conference on Big Data, BigData 2024
Country/TerritoryUnited States
CityWashington
Period15/12/2418/12/24

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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