Thumbs Up and Down: Sentiment Analysis of Medical Online Forums

Victoria Bobicev, Marina Sokolova


Abstract
In the current study, we apply multi-class and multi-label sentence classification to sentiment analysis of online medical forums. We aim to identify major health issues discussed in online social media and the types of sentiments those issues evoke. We use ontology of personal health information for Information Extraction and apply Machine Learning methods in automated recognition of the expressed sentiments.
Anthology ID:
W18-5906
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
Venues:
EMNLP | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
22–26
Language:
URL:
https://aclanthology.org/W18-5906
DOI:
10.18653/v1/W18-5906
Bibkey:
Cite (ACL):
Victoria Bobicev and Marina Sokolova. 2018. Thumbs Up and Down: Sentiment Analysis of Medical Online Forums. In Proceedings of the 2018 EMNLP Workshop SMM4H: The 3rd Social Media Mining for Health Applications Workshop & Shared Task, pages 22–26, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
Thumbs Up and Down: Sentiment Analysis of Medical Online Forums (Bobicev & Sokolova, 2018)
Copy Citation:
PDF:
https://aclanthology.org/W18-5906.pdf