Offline events and online hate

Online hate speech is a critical and worsening problem, with extremists using social media platforms to radicalize recruits and coordinate offline violent events. While much progress has been made in analyzing online hate speech, no study to date has classified multiple types of hate speech across b...

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Bibliographic Details
Published in:PloS one 2023-01, Vol.18 (1), p.e0278511-e0278511
Main Authors: Lupu, Yonatan, Sear, Richard, Velásquez, Nicolas, Leahy, Rhys, Restrepo, Nicholas Johnson, Goldberg, Beth, Johnson, Neil F
Format: Article
Language:English
Subjects:
Aggression
Analysis
Biology and Life Sciences
Computer and Information Sciences
Ecology and Environmental Sciences
Elections
Hate
Hate speech
Humans
Influence
Internet
Machine learning
Methods
People and Places
Psychological aspects
Radicals
Social aspects
Social Media
Social networks
Social Sciences
Speech
Supervised learning
Violence
Virtual communities
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Summary:Online hate speech is a critical and worsening problem, with extremists using social media platforms to radicalize recruits and coordinate offline violent events. While much progress has been made in analyzing online hate speech, no study to date has classified multiple types of hate speech across both mainstream and fringe platforms. We conduct a supervised machine learning analysis of 7 types of online hate speech on 6 interconnected online platforms. We find that offline trigger events, such as protests and elections, are often followed by increases in types of online hate speech that bear seemingly little connection to the underlying event. This occurs on both mainstream and fringe platforms, despite moderation efforts, raising new research questions about the relationship between offline events and online speech, as well as implications for online content moderation.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0278511