Use of social media for the detection and analysis of infectious diseases in China

Xinyue Ye, Shengwen Li, Xining Yang, Chenglin Qin

Research output: Contribution to journalArticlepeer-review

54 Scopus citations


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 fromWeibo. 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.

Original languageEnglish (US)
Article number156
JournalISPRS International Journal of Geo-Information
Issue number9
StatePublished - Sep 2016
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Geography, Planning and Development
  • Computers in Earth Sciences
  • Earth and Planetary Sciences (miscellaneous)


  • China
  • Infectious disease
  • Social media
  • Space
  • Time


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