Abstract
This is a description of our participation in the ADE Mining in English Tweets shared task, organized by the Social Media Mining for Health SMM4H 2022 workshop. We participate in the subtask a of shared Task 1, and the paper introduces the system we developed for solving the task. The task requires classifying the given tweets by whether they mention the Adverse Drug Effects. We utilize RoBERTa model and apply several methods during training and finetuning period. We also try to improve the performance of our system by preprocessing the dataset but improve the precision only. The results of our system on test set are 0.601 in F1- score, 0.705 in precision, and 0.524 in recall.- Anthology ID:
- 2022.smm4h-1.10
- Volume:
- Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task
- Month:
- October
- Year:
- 2022
- Address:
- Gyeongju, Republic of Korea
- Editors:
- Graciela Gonzalez-Hernandez, Davy Weissenbacher
- Venue:
- SMM4H
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 35–37
- Language:
- URL:
- https://aclanthology.org/2022.smm4h-1.10
- DOI:
- Cite (ACL):
- Chunchen Wei, Ran Bi, and Yanru Zhang. 2022. uestcc@SMM4H’22: RoBERTa based Adverse Drug Events Classification on Tweets. In Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task, pages 35–37, Gyeongju, Republic of Korea. Association for Computational Linguistics.
- Cite (Informal):
- uestcc@SMM4H’22: RoBERTa based Adverse Drug Events Classification on Tweets (Wei et al., SMM4H 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2022.smm4h-1.10.pdf