DUTH at SemEval-2023 Task 9: An Ensemble Approach for Twitter Intimacy Analysis
Giorgos Arampatzis, Vasileios Perifanis, Symeon Symeonidis, Avi Arampatzis
Abstract
This work presents the approach developed by the DUTH team for participating in the SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis. Our results show that pre-processing techniques do not affect the learning performance for the task of multilingual intimacy analysis. In addition, we show that fine-tuning a transformer-based model does not provide advantages over using the pre-trained model to generate text embeddings and using the resulting representations to train simpler and more efficient models such as MLP. Finally, we utilize an ensemble of classifiers, including three MLPs with different architectures and a CatBoost model, to improve the regression accuracy.- Anthology ID:
- 2023.semeval-1.170
- 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:
- 1225–1230
- Language:
- URL:
- https://aclanthology.org/2023.semeval-1.170
- DOI:
- 10.18653/v1/2023.semeval-1.170
- Cite (ACL):
- Giorgos Arampatzis, Vasileios Perifanis, Symeon Symeonidis, and Avi Arampatzis. 2023. DUTH at SemEval-2023 Task 9: An Ensemble Approach for Twitter Intimacy Analysis. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 1225–1230, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- DUTH at SemEval-2023 Task 9: An Ensemble Approach for Twitter Intimacy Analysis (Arampatzis et al., SemEval 2023)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2023.semeval-1.170.pdf