Social media mining for public health monitoring and surveillance

Michael J. Paul, Abeed Sarker, John S. Brownstein, Azadeh Nikfarjam, Matthew Scotch, Karen L. Smith, Graciela Gonzalez

Research output: Chapter in Book/Report/Conference proceedingConference contribution

39 Scopus citations

Abstract

This paper describes topics pertaining to the session, “Social Media Mining for Public Health Monitoring and Surveillance,” at the Pacific Symposium on Biocomputing (PSB) 2016. In addition to summarizing the content of the session, this paper also surveys recent research on using social media data to study public health. The survey is organized into sections describing recent progress in public health problems, computational methods, and social implications.

Original languageEnglish (US)
Title of host publicationPacific Symposium on Biocomputing 2016, PSB 2016
PublisherWorld Scientific Publishing Co. Pte Ltd
Pages468-479
Number of pages12
StatePublished - 2016
Event21st Pacific Symposium on Biocomputing, PSB 2016 - Big Island, United States
Duration: Jan 4 2016Jan 8 2016

Other

Other21st Pacific Symposium on Biocomputing, PSB 2016
CountryUnited States
CityBig Island
Period1/4/161/8/16

Keywords

  • Data mining
  • Natural language processing
  • Public health
  • Social media

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Biomedical Engineering

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  • Cite this

    Paul, M. J., Sarker, A., Brownstein, J. S., Nikfarjam, A., Scotch, M., Smith, K. L., & Gonzalez, G. (2016). Social media mining for public health monitoring and surveillance. In Pacific Symposium on Biocomputing 2016, PSB 2016 (pp. 468-479). World Scientific Publishing Co. Pte Ltd.