FBK@SMM4H2020: RoBERTa for Detecting Medications on Twitter

Silvia Casola, Alberto Lavelli


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:
Bibkey:
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)
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PDF:
https://aclanthology.org/2020.smm4h-1.15.pdf