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Identifying Diseases, Drugs, and Symptoms in Twitter.
- Source :
- Medinfo; 2015, p643-647, 5p
- Publication Year :
- 2015
-
Abstract
- Social media sites, such as Twitter, are a rich source of many kinds of information, including health-related information. Accurate detection of entities such as diseases, drugs, and symptoms could be used for biosurveillance (e.g. monitoring of flu) and identification of adverse drug events. However, a critical assessment of performance of current text mining technology on Twitter has not been done yet in the medical domain. Here, we study the development of a Twitter data set annotated with relevant medical entities which we have publicly released. The manual annotation results show that it is possible to perform high-quality annotation despite of the complexity of medical terminology and the lack of context in a tweet. Furthermore, we have evaluated the capability of state-of-the-art approaches to reproduce the annotations in the data set. The best methods achieve F-scores of 55-66%. The data analysis and the preliminary results provide valuable insights on identifying medical entities in Twitter for various applications. [ABSTRACT FROM AUTHOR]
- Subjects :
- SOCIAL media
MEDICAL terminology
MEDICAL equipment
MEDICAL care
Subjects
Details
- Language :
- English
- ISSN :
- 15696332
- Database :
- Complementary Index
- Journal :
- Medinfo
- Publication Type :
- Conference
- Accession number :
- 114400224
- Full Text :
- https://doi.org/10.3233/978-1-61499-564-7-643