mlsanityData to 14 Oct 2026

Factoring Hate Speech: A New Annotation Framework to Study Hate Speech in Social Media

arXiv 2311.03969 ↗First posted 7 Nov 2023cs.CLcited by 5

Not on the map. Why?

Abstract (arXiv)

In this work we propose a novel annotation scheme which factors hate speech into five separate discursive categories. To evaluate our scheme, we construct a corpus of over 2.9M Twitter posts containing hateful expressions directed at Jews, and annotate a sample dataset of 1,050 tweets. We present a statistical analysis of the annotated dataset as well as discuss annotation examples, and conclude by discussing promising directions for future work.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 9 of its 20 references that are in the map. First posted on arXiv 7 Nov 2023.

Builds on

9 of 20 references.

References · 9

  1. 2017Automated Hate Speech Detection and the Problem of Offensive Languagecited by 736
  2. 2020HateXplain: A Benchmark Dataset for Explainable Hate Speech Detectioncited by 407
  3. 2018Large Scale Crowdsourcing and Characterization of Twitter Abusive Behaviorcited by 270
  4. 2017Understanding Abuse: A Typology of Abusive Language Detection Subtaskscited by 116
  5. 2018Peer to Peer Hate: Hate Speech Instigators and Their Targetscited by 30
  6. 2020Countering hate on social media: Large scale classification of hate and counter speechcited by 22
  7. 2021"Subverting the Jewtocracy": Online Antisemitism Detection Using Multimodal Deep Learningcited by 21
  8. 2022Hate Speech Criteria: A Modular Approach to Task-Specific Hate Speech Definitionscited by 18
  9. 2020Does Terrorism Trigger Online Hate Speech? On the Association of Events and Time Seriescited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 3; 2026: 1.

5 papers.