ArticlePloS one2023
Offline events and online hate.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed.
- Listen to Me! Target Perceptions of Digital Hate: A Scoping Review of Recent Research.Trauma, violence & abuse · 2025Article
- Ideology and polarization set the agenda on social media.Scientific reports · 2025Article
- Tracking patterns in toxicity and antisocial behavior over user lifetimes on large social media platforms.Scientific reports · 2025Article
- Infodemic Versus Viral Information Spread: Key Differences and Open Challenges.JMIR infodemiology · 2025Article
- Article
- Patterns of linguistic simplification on social media platforms over time.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Online communities come with real-world consequences for individuals and societies.Communications psychology · 2024Review
- Article
- How U.S. Presidential elections strengthen global hate networks.Npj complexity · 2024Article
- Controlling bad-actor-artificial intelligence activity at scale across online battlefields.PNAS nexus · 2024Article
- A normalization model for repeated letters in social media hate speech text based on rules and spelling correction.PloS one · 2024Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.