Text Augmentation Techniques in Drug Adverse Effect Detection Task

Pavel Blinov


Abstract
The paper researches the problem of drug adverse effect detection in texts of social media. We describe the development of such classification system for Russian tweets. To increase the train dataset we apply a couple of augmentation techniques and analyze their effect in comparison with similar systems presented at 2021 years’ SMM4H Workshop.
Anthology ID:
2021.smm4h-1.17
Volume:
Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task
Month:
June
Year:
2021
Address:
Mexico City, Mexico
Editors:
Arjun Magge, Ari Klein, Antonio Miranda-Escalada, Mohammed Ali Al-garadi, Ilseyar Alimova, Zulfat Miftahutdinov, Eulalia Farre-Maduell, Salvador Lima Lopez, Ivan Flores, Karen O'Connor, Davy Weissenbacher, Elena Tutubalina, Abeed Sarker, Juan M Banda, Martin Krallinger, Graciela Gonzalez-Hernandez
Venue:
SMM4H
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
95–97
Language:
URL:
https://aclanthology.org/2021.smm4h-1.17
DOI:
10.18653/v1/2021.smm4h-1.17
Bibkey:
Cite (ACL):
Pavel Blinov. 2021. Text Augmentation Techniques in Drug Adverse Effect Detection Task. In Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task, pages 95–97, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
Text Augmentation Techniques in Drug Adverse Effect Detection Task (Blinov, SMM4H 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.smm4h-1.17.pdf