Hatemoji: A Test Suite and Adversarially-Generated Dataset for Benchmarking and Detecting Emoji-Based Hate
Hannah Kirk, Bertie Vidgen, Paul Rottger, Tristan Thrush, Scott Hale
Abstract
Detecting online hate is a complex task, and low-performing models have harmful consequences when used for sensitive applications such as content moderation. Emoji-based hate is an emerging challenge for automated detection. We present HatemojiCheck, a test suite of 3,930 short-form statements that allows us to evaluate performance on hateful language expressed with emoji. Using the test suite, we expose weaknesses in existing hate detection models. To address these weaknesses, we create the HatemojiBuild dataset using a human-and-model-in-the-loop approach. Models built with these 5,912 adversarial examples perform substantially better at detecting emoji-based hate, while retaining strong performance on text-only hate. Both HatemojiCheck and HatemojiBuild are made publicly available.- Anthology ID:
- 2022.naacl-main.97
- Volume:
- Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
- Month:
- July
- Year:
- 2022
- Address:
- Seattle, United States
- Editors:
- Marine Carpuat, Marie-Catherine de Marneffe, Ivan Vladimir Meza Ruiz
- Venue:
- NAACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1352–1368
- Language:
- URL:
- https://aclanthology.org/2022.naacl-main.97
- DOI:
- 10.18653/v1/2022.naacl-main.97
- Cite (ACL):
- Hannah Kirk, Bertie Vidgen, Paul Rottger, Tristan Thrush, and Scott Hale. 2022. Hatemoji: A Test Suite and Adversarially-Generated Dataset for Benchmarking and Detecting Emoji-Based Hate. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 1352–1368, Seattle, United States. Association for Computational Linguistics.
- Cite (Informal):
- Hatemoji: A Test Suite and Adversarially-Generated Dataset for Benchmarking and Detecting Emoji-Based Hate (Kirk et al., NAACL 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/2022.naacl-main.97.pdf
- Code
- HannahKirk/Hatemoji
- Data
- HatemojiCheck