Abstract
Natural language processing research has begun to embrace the notion of annotator subjectivity, motivated by variations in labelling. This approach understands each annotator’s view as valid, which can be highly suitable for tasks that embed subjectivity, e.g., sentiment analysis. However, this construction may be inappropriate for tasks such as hate speech detection, as it affords equal validity to all positions on e.g., sexism or racism. We argue that the conflation of hate and offence can invalidate findings on hate speech, and call for future work to be situated in theory, disentangling hate from its orthogonal concept, offence.- Anthology ID:
- 2024.woah-1.22
- Volume:
- Proceedings of the 8th Workshop on Online Abuse and Harms (WOAH 2024)
- Month:
- June
- Year:
- 2024
- Address:
- Mexico City, Mexico
- Editors:
- Yi-Ling Chung, Zeerak Talat, Debora Nozza, Flor Miriam Plaza-del-Arco, Paul Röttger, Aida Mostafazadeh Davani, Agostina Calabrese
- Venues:
- WOAH | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 275–282
- Language:
- URL:
- https://aclanthology.org/2024.woah-1.22
- DOI:
- Cite (ACL):
- Amanda Cercas Curry, Gavin Abercrombie, and Zeerak Talat. 2024. Subjective Isms? On the Danger of Conflating Hate and Offence in Abusive Language Detection. In Proceedings of the 8th Workshop on Online Abuse and Harms (WOAH 2024), pages 275–282, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- Subjective Isms? On the Danger of Conflating Hate and Offence in Abusive Language Detection (Cercas Curry et al., WOAH-WS 2024)
- PDF:
- https://preview.aclanthology.org/jeptaln-2024-ingestion/2024.woah-1.22.pdf