# A Weakly Supervised Classifier and Dataset of White Supremacist Language

arXiv: https://arxiv.org/abs/2306.15732 · HTML: https://mlsanity.com/paper/2306.15732/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 18 of its 79 references that are in the map.
- First posted on arXiv 27 Jun 2023.

## Builds on (most cited first, 18 of 18)

- [DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter](https://mlsanity.com/paper/1910.01108/) (2019)
- [BERTopic: Neural topic modeling with a class-based TF-IDF procedure](https://mlsanity.com/paper/2203.05794/) (2022)
- [Snorkel: Rapid Training Data Creation with Weak Supervision](https://mlsanity.com/paper/1711.10160/) (2017)
- [Latent Hatred: A Benchmark for Understanding Implicit Hate Speech](https://mlsanity.com/paper/2109.05322/) (2021)
- [HateCheck: Functional Tests for Hate Speech Detection Models](https://mlsanity.com/paper/2012.15606/) (2020)
- [Racial Bias in Hate Speech and Abusive Language Detection Datasets](https://mlsanity.com/paper/1905.12516/) (2019)
- [Hate Speech Dataset from a White Supremacy Forum](https://mlsanity.com/paper/1809.04444/) (2018)
- [Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure](https://mlsanity.com/paper/2010.13561/) (2020)
- [A BERT-Based Transfer Learning Approach for Hate Speech Detection in Online Social Media](https://mlsanity.com/paper/1910.12574/) (2019)
- [Self-Training with Weak Supervision](https://mlsanity.com/paper/2104.05514/) (2021)
- [Disembodied Machine Learning: On the Illusion of Objectivity in NLP](https://mlsanity.com/paper/2101.11974/) (2021)
- [Raiders of the Lost Kek: 3.5 Years of Augmented 4chan Posts from the Politically Incorrect Board](https://mlsanity.com/paper/2001.07487/) (2020)
- [How Hate Speech Varies by Target Identity: A Computational Analysis](https://mlsanity.com/paper/2210.10839/) (2022)
- [Detecting White Supremacist Hate Speech using Domain Specific Word Embedding with Deep Learning and BERT](https://mlsanity.com/paper/2010.00357/) (2020)
- [Reinforcement Guided Multi-Task Learning Framework for Low-Resource Stereotype Detection](https://mlsanity.com/paper/2203.14349/) (2022)
- [Hierarchical CVAE for Fine-Grained Hate Speech Classification](https://mlsanity.com/paper/1809.00088/) (2018)
- [A Bootstrapped Model to Detect Abuse and Intent in White Supremacist Corpora](https://mlsanity.com/paper/2008.04276/) (2020)
- [AX-MABSA: A Framework for Extremely Weakly Supervised Multi-label Aspect Based Sentiment Analysis](https://mlsanity.com/paper/2211.03837/) (2022)

## Built on by (most cited first, 1 of 1)

- [Modeling the Sacred: Considerations when Using Religious Texts in Natural Language Processing](https://mlsanity.com/paper/2404.14740/) (2024)

## Abstract (arXiv)

We present a dataset and classifier for detecting the language of white supremacist extremism, a growing issue in online hate speech. Our weakly supervised classifier is trained on large datasets of text from explicitly white supremacist domains paired with neutral and anti-racist data from similar domains. We demonstrate that this approach improves generalization performance to new domains. Incorporating anti-racist texts as counterexamples to white supremacist language mitigates bias.