Abstract
This paper describes the system that participated in the Climate Activism Stance and Hate Event Detection shared task organized at The 7th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2024). The system tackles the important task of hate speech detection by combining large language model predictions with manually designed features, while trying to explain where the LLM approach fails to predict the correct results.- Anthology ID:
- 2024.case-1.8
- Volume:
- Proceedings of the 7th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2024)
- Month:
- March
- Year:
- 2024
- Address:
- St. Julians, Malta
- Editors:
- Ali Hürriyetoğlu, Hristo Tanev, Surendrabikram Thapa, Gökçe Uludoğan
- Venues:
- CASE | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 67–72
- Language:
- URL:
- https://aclanthology.org/2024.case-1.8
- DOI:
- Cite (ACL):
- Vasile Păiș. 2024. RACAI at ClimateActivism 2024: Improving Detection of Hate Speech by Extending LLM Predictions with Handcrafted Features. In Proceedings of the 7th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2024), pages 67–72, St. Julians, Malta. Association for Computational Linguistics.
- Cite (Informal):
- RACAI at ClimateActivism 2024: Improving Detection of Hate Speech by Extending LLM Predictions with Handcrafted Features (Păiș, CASE-WS 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.case-1.8.pdf