Abstract
Social media platforms like Twitter - recently rebranded as X - produce nearly half a billion tweets daily and host a significant number of users that can be affected by content that are not properly moderated. In this work, we present an approach that ranked third at the HSD-2Lang 2024 competition’s subtask-A along with additional methodology developed for this task and evaluation of different approaches. We utilize three different models and the best performing approach use publicly-available TurkishBERTweet model with low-rank adaptation (LoRA) for fine tuning. We also experiment with another publicly available model and a novel methodology to ensemble different hand-crafted features and outcomes of different models. Finally, we report the experimental results, competition scores, and discussion to improve this effort further.- Anthology ID:
- 2024.case-1.25
- 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:
- 185–189
- Language:
- URL:
- https://aclanthology.org/2024.case-1.25
- DOI:
- Cite (ACL):
- Ali Najafi and Onur Varol. 2024. VRLLab at HSD-2Lang 2024: Turkish Hate Speech Detection Online with TurkishBERTweet. In Proceedings of the 7th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2024), pages 185–189, St. Julians, Malta. Association for Computational Linguistics.
- Cite (Informal):
- VRLLab at HSD-2Lang 2024: Turkish Hate Speech Detection Online with TurkishBERTweet (Najafi & Varol, CASE-WS 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/2024.case-1.25.pdf