Abstract
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.- Anthology ID:
- 2023.woah-1.21
- Volume:
- The 7th Workshop on Online Abuse and Harms (WOAH)
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Yi-ling Chung, Paul R{\"ottger}, Debora Nozza, Zeerak Talat, Aida Mostafazadeh Davani
- Venue:
- WOAH
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 215–220
- Language:
- URL:
- https://aclanthology.org/2023.woah-1.21
- DOI:
- 10.18653/v1/2023.woah-1.21
- Cite (ACL):
- Gal Ron, Effi Levi, Odelia Oshri, and Shaul Shenhav. 2023. Factoring Hate Speech: A New Annotation Framework to Study Hate Speech in Social Media. In The 7th Workshop on Online Abuse and Harms (WOAH), pages 215–220, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- Factoring Hate Speech: A New Annotation Framework to Study Hate Speech in Social Media (Ron et al., WOAH 2023)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2023.woah-1.21.pdf