research-article

Auditing radicalization pathways on YouTube

Authors:

Manoel Horta Ribeiro,

Raphael Ottoni,

Virgílio A. F. Almeida,

Wagner Meira, Jr.Authors Info & Claims

FAT* '20: Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency

Pages 131 - 141

https://doi.org/10.1145/3351095.3372879

Published: 27 January 2020 Publication History

Abstract

Non-profits, as well as the media, have hypothesized the existence of a radicalization pipeline on YouTube, claiming that users systematically progress towards more extreme content on the platform. Yet, there is to date no substantial quantitative evidence of this alleged pipeline. To close this gap, we conduct a large-scale audit of user radicalization on YouTube. We analyze 330,925 videos posted on 349 channels, which we broadly classified into four types: Media, the Alt-lite, the Intellectual Dark Web (I.D.W.), and the Alt-right. According to the aforementioned radicalization hypothesis, channels in the I.D.W. and the Alt-lite serve as gateways to fringe far-right ideology, here represented by Alt-right channels. Processing 72M+ comments, we show that the three channel types indeed increasingly share the same user base; that users consistently migrate from milder to more extreme content; and that a large percentage of users who consume Alt-right content now consumed Alt-lite and I.D.W. content in the past. We also probe YouTube's recommendation algorithm, looking at more than 2M video and channel recommendations between May/July 2019. We find that Alt-lite content is easily reachable from I.D.W. channels, while Alt-right videos are reachable only through channel recommendations. Overall, we paint a comprehensive picture of user radicalization on YouTube.

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Cited By

Ditlhokwa G(2024)Unlocking Monetization Potential in the Age of YouTube Algorithmic Bias: An Analysis of Botswana FilmmakingThe Future of Television and Video Industry10.5772/intechopen.113306Online publication date: 12-Jun-2024
https://doi.org/10.5772/intechopen.113306
Capelos TSalmela MTalalakina ACotena O(2024)Ressentiment in the Manosphere: Conceptions of Morality and Avenues for Resistance in the Incel Hatred PipelinePhilosophies10.3390/philosophies90200369:2(36)Online publication date: 13-Mar-2024
https://doi.org/10.3390/philosophies9020036
Bondi TRafieian OYao a(2024)Privacy and Polarization: An Inference-Based FrameworkSSRN Electronic Journal10.2139/ssrn.4641822Online publication date: 2024
https://doi.org/10.2139/ssrn.4641822
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Index Terms

Auditing radicalization pathways on YouTube
1. Human-centered computing
  1. Collaborative and social computing
    1. Empirical studies in collaborative and social computing

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cover image ACM Conferences

FAT* '20: Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency

January 2020

895 pages

ISBN:9781450369367

DOI:10.1145/3351095

Copyright © 2020 ACM.

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Published: 27 January 2020

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Cited By

Ditlhokwa G(2024)Unlocking Monetization Potential in the Age of YouTube Algorithmic Bias: An Analysis of Botswana FilmmakingThe Future of Television and Video Industry10.5772/intechopen.113306Online publication date: 12-Jun-2024
https://doi.org/10.5772/intechopen.113306
Capelos TSalmela MTalalakina ACotena O(2024)Ressentiment in the Manosphere: Conceptions of Morality and Avenues for Resistance in the Incel Hatred PipelinePhilosophies10.3390/philosophies90200369:2(36)Online publication date: 13-Mar-2024
https://doi.org/10.3390/philosophies9020036
Bondi TRafieian OYao a(2024)Privacy and Polarization: An Inference-Based FrameworkSSRN Electronic Journal10.2139/ssrn.4641822Online publication date: 2024
https://doi.org/10.2139/ssrn.4641822
Karas T(2024)Cultural criminology, counter-extremism and the contemporary far rightCrime, Media, Culture: An International Journal10.1177/17416590241279413Online publication date: 17-Sep-2024
https://doi.org/10.1177/17416590241279413
Shin DJitkajornwanich K(2024)How Algorithms Promote Self-Radicalization: Audit of TikTok’s Algorithm Using a Reverse Engineering MethodSocial Science Computer Review10.1177/0894439323122554742:4(1020-1040)Online publication date: 30-Jul-2024
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Godinez LMustafaraj E(2024)YouTube and Conspiracy Theories: A Longitudinal Audit of Information PanelsProceedings of the 35th ACM Conference on Hypertext and Social Media10.1145/3648188.3675128(273-284)Online publication date: 10-Sep-2024
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Chee JKalyanaraman SErnala SWeinsberg UDean SIoannidis SBaeza-Yates RBonchi F(2024)Harm Mitigation in Recommender Systems under User Preference DynamicsProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671925(255-265)Online publication date: 25-Aug-2024
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Nigatu HRaji I(2024)“I Searched for a Religious Song in Amharic and Got Sexual Content Instead’’: Investigating Online Harm in Low-Resourced Languages on YouTube.Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency10.1145/3630106.3658546(141-160)Online publication date: 3-Jun-2024
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