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ISPRS Int. J. Geo-Inf. 2016, 5(9), 156; doi:10.3390/ijgi5090156

Use of Social Media for the Detection and Analysis of Infectious Diseases in China

1
Department of Geography, Kent State University, Kent, OH 44240, USA
2
School of Information Engineering, China University of Geosciences, Wuhan 430074, China
3
Department of Geography and Geology, Eastern Michigan University, Ypsilanti, MI 48197, USA
4
School of Economics, Jinan University, Guangzhou 510632, China
*
Author to whom correspondence should be addressed.
Academic Editor: Wolfgang Kainz
Received: 6 February 2016 / Revised: 15 August 2016 / Accepted: 19 August 2016 / Published: 30 August 2016
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Abstract

Social media activity has become an important component of daily life for many people. Messages from Twitter (US) and Weibo (China) have shown their potential as important data sources for detecting and analyzing infectious diseases. Such emerging and dynamic new data sources allow us to predict how infectious diseases develop and evolve both spatially and temporally. We report the dynamics of dengue fever in China using messages from Weibo. We first extract and construct a list of keywords related to dengue fever in order to analyze how frequently these words appear in Weibo messages based on the Latent Dirichlet Allocation (LDA). Spatial analysis is then applied to detect how dengue fever cases cluster spatially and spread over time. View Full-Text
Keywords: social media; infectious disease; space; time; China social media; infectious disease; space; time; China
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Ye, X.; Li, S.; Yang, X.; Qin, C. Use of Social Media for the Detection and Analysis of Infectious Diseases in China. ISPRS Int. J. Geo-Inf. 2016, 5, 156.

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