Abstract
This paper presents our approach to the SemEval-2023 Task 3 to detect online persuasion techniques in a multilingual setup. Our classification system is based on the RoBERTa-base model trained predominantly on English to label the persuasion techniques across 9 different languages. Our system was able to significantly surpass the baseline performance in 3 of the 9 languages: English, Georgian and Greek. However, our wrong assumption that a single classification system trained predominantly on English could generalize well to other languages, negatively impacted our scores on the other 6 languages. In this paper, we provide a description of the reasoning behind the development of our final model and what conclusions may be drawn from its performance for future work.- Anthology ID:
- 2023.semeval-1.223
- Volume:
- Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Atul Kr. Ojha, A. Seza Doğruöz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1613–1618
- Language:
- URL:
- https://aclanthology.org/2023.semeval-1.223
- DOI:
- 10.18653/v1/2023.semeval-1.223
- Cite (ACL):
- Nelson Filipe Costa, Bryce Hamilton, and Leila Kosseim. 2023. CLaC at SemEval-2023 Task 3: Language Potluck RoBERTa Detects Online Persuasion Techniques in a Multilingual Setup. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 1613–1618, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- CLaC at SemEval-2023 Task 3: Language Potluck RoBERTa Detects Online Persuasion Techniques in a Multilingual Setup (Costa et al., SemEval 2023)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2023.semeval-1.223.pdf