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

arXiv: https://arxiv.org/abs/2311.03969 · HTML: https://mlsanity.com/paper/2311.03969/

## 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 (most cited first, 9 of 9)

- [Automated Hate Speech Detection and the Problem of Offensive Language](https://mlsanity.com/paper/1703.04009/) (2017)
- [HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection](https://mlsanity.com/paper/2012.10289/) (2020)
- [Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior](https://mlsanity.com/paper/1802.00393/) (2018)
- [Understanding Abuse: A Typology of Abusive Language Detection Subtasks](https://mlsanity.com/paper/1705.09899/) (2017)
- [Peer to Peer Hate: Hate Speech Instigators and Their Targets](https://mlsanity.com/paper/1804.04649/) (2018)
- [Countering hate on social media: Large scale classification of hate and counter speech](https://mlsanity.com/paper/2006.01974/) (2020)
- ["Subverting the Jewtocracy": Online Antisemitism Detection Using Multimodal Deep Learning](https://mlsanity.com/paper/2104.05947/) (2021)
- [Hate Speech Criteria: A Modular Approach to Task-Specific Hate Speech Definitions](https://mlsanity.com/paper/2206.15455/) (2022)
- [Does Terrorism Trigger Online Hate Speech? On the Association of Events and Time Series](https://mlsanity.com/paper/2004.14733/) (2020)

## Built on by (most cited first, 5 of 5)

- [EkoHate: Abusive Language and Hate Speech Detection for Code-switched Political Discussions on Nigerian Twitter](https://mlsanity.com/paper/2404.18180/) (2024)
- [Dealing with Annotator Disagreement in Hate Speech Classification](https://mlsanity.com/paper/2502.08266/) (2025)
- [Societal AI Research Has Become Less Interdisciplinary](https://mlsanity.com/paper/2506.08738/) (2025)
- [Dialogues of Dissent: Thematic and Rhetorical Dimensions of Hate and Counter-Hate Speech in Social Media Conversations](https://mlsanity.com/paper/2507.20528/) (2025)
- [Evaluating Large Language Models for Antisemitic Incident Classification](https://mlsanity.com/paper/2607.04890/) (2026)

## 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.