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Offline events and online hate.

Yonatan Lupu1,2, Richard Sear3, Nicolas Velásquez4

  • 1Political Science Department, George Washington University, Washington, DC, United States of America.

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Summary
This summary is machine-generated.

Extremists exploit social media for radicalization. This study analyzed online hate speech across platforms, finding offline events increase unrelated online hate, challenging content moderation.

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Area of Science:

  • Computational Social Science
  • Digital Communication
  • Cyberpsychology

Background:

  • Online hate speech is a growing concern, with extremist groups using social media for recruitment and to incite offline violence.
  • Existing research has not comprehensively classified diverse hate speech types across both mainstream and fringe online platforms.

Purpose of the Study:

  • To classify seven distinct types of online hate speech.
  • To analyze hate speech patterns across six interconnected online platforms, including mainstream and fringe sites.
  • To investigate the relationship between offline events and online hate speech dynamics.

Main Methods:

  • Employed supervised machine learning techniques for hate speech classification.
  • Analyzed data from six interconnected online platforms.
  • Examined hate speech trends in relation to offline trigger events like protests and elections.

Main Results:

  • Identified significant increases in specific types of online hate speech following offline events, even when the speech appeared unrelated to the event.
  • Observed these increases on both mainstream and fringe online platforms.
  • Detected these patterns despite ongoing content moderation efforts.

Conclusions:

  • Offline events can trigger surges in seemingly disconnected online hate speech across various platforms.
  • Current content moderation strategies may be insufficient to curb this phenomenon.
  • Further research is needed to understand the complex interplay between offline events and online hate speech, informing future moderation policies.