Are Chess Discussions Racist? An Adversarial Hate Speech Data Set
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Abstract (arXiv)
On June 28, 2020, while presenting a chess podcast on Grandmaster Hikaru Nakamura, Antonio Radi'c's YouTube handle got blocked because it contained "harmful and dangerous" content. YouTube did not give further specific reason, and the channel got reinstated within 24 hours. However, Radi'c speculated that given the current political situation, a referral to "black against white", albeit in the context of chess, earned him this temporary ban. In this paper, via a substantial corpus of 681,995 comments, on 8,818 YouTube videos hosted by five highly popular chess-focused YouTube channels, we ask the following research question: how robust are off-the-shelf hate-speech classifiers to out-of-domain adversarial examples? We release a data set of 1,000 annotated comments where existing hate speech classifiers misclassified benign chess discussions as hate speech. We conclude with an intriguing analogy result on racial bias with our findings pointing out to the broader challenge of color polysemy.
Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Nov 2020.
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Citing papers per year: 2022: 3; 2023: 4; 2024: 3.
10 papers.
- 2024From Languages to Geographies: Towards Evaluating Cultural Bias in Hate Speech Datasetscited by 25
- 2022On the Calibration of Massively Multilingual Language Modelscited by 19
- 2022Hate Speech Criteria: A Modular Approach to Task-Specific Hate Speech Definitionscited by 18
- 2023Vicarious Offense and Noise Audit of Offensive Speech Classifiers: Unifying Human and Machine Disagreement on What is Offensivecited by 16
- 2024Improving Adversarial Data Collection by Supporting Annotators: Lessons from GAHD, a German Hate Speech Datasetcited by 13
- 2022'Beach' to 'Bitch': Inadvertent Unsafe Transcription of Kids' Content on YouTubecited by 3
- 2023Auditing and Robustifying COVID-19 Misinformation Datasets via Anticontent Samplingcited by 3
- 2023LLMs and Finetuning: Benchmarking cross-domain performance for hate speech detectioncited by 3
- 2024Towards Generalized Offensive Language Identificationcited by 1
- 2023On the Challenges of Building Datasets for Hate Speech Detectioncited by 0
- 2024Towards Generalized Offensive Language Identification26 Jul 2024
- 2024From Languages to Geographies: Towards Evaluating Cultural Bias in Hate Speech Datasets27 Apr 2024
- 2024Improving Adversarial Data Collection by Supporting Annotators: Lessons from GAHD, a German Hate Speech Dataset28 Mar 2024
- 2023LLMs and Finetuning: Benchmarking cross-domain performance for hate speech detection29 Oct 2023
- 2023On the Challenges of Building Datasets for Hate Speech Detection6 Sep 2023
- 2023Auditing and Robustifying COVID-19 Misinformation Datasets via Anticontent Sampling5 Aug 2023
- 2023Vicarious Offense and Noise Audit of Offensive Speech Classifiers: Unifying Human and Machine Disagreement on What is Offensive29 Jan 2023
- 2022On the Calibration of Massively Multilingual Language Models21 Oct 2022
- 2022Hate Speech Criteria: A Modular Approach to Task-Specific Hate Speech Definitions30 Jun 2022
- 2022'Beach' to 'Bitch': Inadvertent Unsafe Transcription of Kids' Content on YouTube17 Feb 2022