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

Department of Geography, Kent State University, Kent, OH 44240, USA
School of Information Engineering, China University of Geosciences, Wuhan 430074, China
Department of Geography and Geology, Eastern Michigan University, Ypsilanti, MI 48197, USA
School of Economics, Jinan University, Guangzhou 510632, China
Author to whom correspondence should be addressed.
Academic Editor: Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2016, 5(9), 156;
Received: 6 February 2016 / Revised: 15 August 2016 / Accepted: 19 August 2016 / Published: 30 August 2016
PDF [4776 KB, uploaded 30 August 2016]


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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