Extracting health-related causality from twitter messages using natural language processing

Extracting health-related causality from twitter messages using natural language processing

Abstract Background Twitter messages (tweets) contain various types of topics in our daily life, which include health-related topics. Analysis of health-related tweets would help us understand health conditions and concerns encountered in our daily lives. In this paper we evaluate an approach to ext...

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Bibliographic Details
Main Authors: Son Doan, Elly W. Yang, Sameer S. Tilak, Peter W. Li, Daniel S. Zisook, Manabu Torii
Format: Article
Language:English
Published: BMC 2019-04-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Twitter
Causality
Causal relationships
Cause-effect
Natural language processing (NLP)
Online Access:http://link.springer.com/article/10.1186/s12911-019-0785-0

Internet

http://link.springer.com/article/10.1186/s12911-019-0785-0

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