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PLoS One. 2014 Jan 29;9(1):e86191. doi: 10.1371/journal.pone.0086191. eCollection 2014.

Twitter: a good place to detect health conditions.

Author information

1
Department of Information and Communication Technologies, Campus Elviña s/n, Coruña, Spain.
2
University of Aveiro, DETI/IEETA, Campus Universitariá de Santiago, Aveiro, Portugal.

Abstract

With the proliferation of social networks and blogs, the Internet is increasingly being used to disseminate personal health information rather than just as a source of information. In this paper we exploit the wealth of user-generated data, available through the micro-blogging service Twitter, to estimate and track the incidence of health conditions in society. The method is based on two stages: we start by extracting possibly relevant tweets using a set of specially crafted regular expressions, and then classify these initial messages using machine learning methods. Furthermore, we selected relevant features to improve the results and the execution times. To test the method, we considered four health states or conditions, namely flu, depression, pregnancy and eating disorders, and two locations, Portugal and Spain. We present the results obtained and demonstrate that the detection results and the performance of the method are improved after feature selection. The results are promising, with areas under the receiver operating characteristic curve between 0.7 and 0.9, and f-measure values around 0.8 and 0.9. This fact indicates that such approach provides a feasible solution for measuring and tracking the evolution of health states within the society.

PMID:
24489699
PMCID:
PMC3906034
DOI:
10.1371/journal.pone.0086191
[Indexed for MEDLINE]
Free PMC Article

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