Dealing with Medication Non-Adherence Expressions in Twitter
Takeshi Onishi, Davy Weissenbacher, Ari Klein, Karen O’Connor, Graciela Gonzalez-Hernandez
Abstract
Through a semi-automatic analysis of tweets, we show that Twitter users not only express Medication Non-Adherence (MNA) in social media but also their reasons for not complying; further research is necessary to fully extract automatically and analyze this information, in order to facilitate the use of this data in epidemiological studies.- Anthology ID:
- W18-5908
- Volume:
- Proceedings of the 2018 EMNLP Workshop SMM4H: The 3rd Social Media Mining for Health Applications Workshop & Shared Task
- Month:
- October
- Year:
- 2018
- Address:
- Brussels, Belgium
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 32–33
- Language:
- URL:
- https://aclanthology.org/W18-5908
- DOI:
- 10.18653/v1/W18-5908
- Cite (ACL):
- Takeshi Onishi, Davy Weissenbacher, Ari Klein, Karen O’Connor, and Graciela Gonzalez-Hernandez. 2018. Dealing with Medication Non-Adherence Expressions in Twitter. In Proceedings of the 2018 EMNLP Workshop SMM4H: The 3rd Social Media Mining for Health Applications Workshop & Shared Task, pages 32–33, Brussels, Belgium. Association for Computational Linguistics.
- Cite (Informal):
- Dealing with Medication Non-Adherence Expressions in Twitter (Onishi et al., EMNLP 2018)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/W18-5908.pdf