mlsanityData to 7 Oct 2026

Hatemongers ride on echo chambers to escalate hate speech diffusion

arXiv 2302.02479 ↗First posted 5 Feb 2023cs.SI cs.AI cs.CLcited by 4

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Abstract (arXiv)

Recent years have witnessed a swelling rise of hateful and abusive content over online social networks. While detection and moderation of hate speech have been the early go-to countermeasures, the solution requires a deeper exploration of the dynamics of hate generation and propagation. We analyze more than 32 million posts from over 6.8 million users across three popular online social networks to investigate the interrelations between hateful behavior, information dissemination, and polarised organization mediated by echo chambers. We find that hatemongers play a more crucial role in governing the spread of information compared to singled-out hateful content. This observation holds for both the growth of information cascades as well as the conglomeration of hateful actors. Dissection of the core-wise distribution of these networks points towards the fact that hateful users acquire a more well-connected position in the social network and often flock together to build up information cascades. We observe that this cohesion is far from mere organized behavior; instead, in these networks, hatemongers dominate the echo chambers -- groups of users actively align themselves to specific ideological positions. The observed dominance of hateful users to inflate information cascades is primarily via user interactions amplified within these echo chambers. We conclude our study with a cautionary note that popularity-based recommendation of content is susceptible to be exploited by hatemongers given their potential to escalate content popularity via echo-chambered interactions.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 16 of its 58 references that are in the map. First posted on arXiv 5 Feb 2023.

Builds on

16 of 58 references.

References · 16

  1. 2018UMAP: Uniform Manifold Approximation and Projection for Dimension Reductioncited by 2,841
  2. 2017Automated Hate Speech Detection and the Problem of Offensive Languagecited by 724
  3. 2018Universal Sentence Encodercited by 485
  4. 2020Top2Vec: Distributed Representations of Topicscited by 124
  5. 2018Spread of hate speech in online social mediacited by 59
  6. 2021Algorithmic Amplification of Politics on Twittercited by 38
  7. 2018A Unified Deep Learning Architecture for Abuse Detectioncited by 37
  8. 2018Hate Speech Detection: A Solved Problem? The Challenging Case of Long Tail on Twittercited by 36
  9. 2018Political Discourse on Social Media: Echo Chambers, Gatekeepers, and the Price of Bipartisanshipcited by 34
  10. 2018What is Gab? A Bastion of Free Speech or an Alt-Right Echo Chamber?cited by 24
  11. 2018Me, My Echo Chamber, and I: Introspection on Social Media Polarizationcited by 20
  12. 2020Hate is the New Infodemic: A Topic-aware Modeling of Hate Speech Diffusion on Twittercited by 16
4 more
  1. 2021Lifelong Learning of Hate Speech Classification on Social Mediacited by 14
  2. 2020Effectiveness of dismantling strategies on moderated vs. unmoderated online social platformscited by 3
  3. 2020Extremist ideology as a complex contagion: the spread of far-right radicalization in the United States between 2005-2017cited by 2
  4. 2022Making a Radical Misogynist: How online social engagement with the Manosphere influences traits of radicalizationcited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 1; 2025: 0; 2026: 1.

4 papers.