Abstract
This paper describes a classifier for tweets that mention medications or supplements, based on a pretrained transformer. We developed such a system for our participation in Subtask 1 of the Social Media Mining for Health Application workshop, which featured an extremely unbalanced dataset. The model showed promising results, with an F1 of 0.8 (task mean: 0.66).- Anthology ID:
- 2020.smm4h-1.15
- Volume:
- Proceedings of the Fifth Social Media Mining for Health Applications Workshop & Shared Task
- Month:
- December
- Year:
- 2020
- Address:
- Barcelona, Spain (Online)
- Editors:
- Graciela Gonzalez-Hernandez, Ari Z. Klein, Ivan Flores, Davy Weissenbacher, Arjun Magge, Karen O'Connor, Abeed Sarker, Anne-Lyse Minard, Elena Tutubalina, Zulfat Miftahutdinov, Ilseyar Alimova
- Venue:
- SMM4H
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 101–103
- Language:
- URL:
- https://aclanthology.org/2020.smm4h-1.15
- DOI:
- Cite (ACL):
- Silvia Casola and Alberto Lavelli. 2020. FBK@SMM4H2020: RoBERTa for Detecting Medications on Twitter. In Proceedings of the Fifth Social Media Mining for Health Applications Workshop & Shared Task, pages 101–103, Barcelona, Spain (Online). Association for Computational Linguistics.
- Cite (Informal):
- FBK@SMM4H2020: RoBERTa for Detecting Medications on Twitter (Casola & Lavelli, SMM4H 2020)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2020.smm4h-1.15.pdf