Using Twitter to Detect and Investigate Disease Outbreaks | Zendy

David J. Marchette | Zendy; Elizabeth Leeds Hohman | Zendy

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Using Twitter to Detect and Investigate Disease Outbreaks

Author(s) -

David J. Marchette,

Elizabeth Leeds Hohman

Publication year - 2015

Publication title -

online journal of public health informatics

Language(s) - English

Resource type - Journals

ISSN - 1947-2579

DOI - 10.5210/ojphi.v7i1.5813

Subject(s) - computer science , data science , disease surveillance , social media , set (abstract data type) , data set , disease , outbreak , theme (computing) , medicine , world wide web , artificial intelligence , pathology , programming language

We discuss our efforts in detection and tracking using Twitter data collected from January 2013 to the present and discuss various issues that arise in using Twitter data. We discuss various keyword methods, as well as methods for classifying a user as "sick". We discuss some of our successes and failures and provide some insight into the utility and limitations of Twitter. We discuss variations on the basic surveillance theme such as watching for a known disease, a known set of symptoms, and the more general problem of detecting an unusual number of sick individuals within a county.

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