The UNT College of Engineering strives to educate and train engineers and technologists who have the vision to recognize and solve the problems of society. The college comprises six degree-granting departments of instruction and research.
This article discusses text and structural data mining of influenza mentions in web and social media.
Physical Description
20 p.
Notes
Abstract: Text and structural data mining of web and social media (WSM) provides a novel disease surveillance resource and can identify online communities for targeted public health communications (PHC) to assure wide dissemination of pertinent information. WSM that mention influenza are harvested over a 24-week period, 5 October 2008 to 21 March 2009. Link analysis reveals communities for targeted PHC. Text mining is shown to identify trends in flu posts that correlate to real-world influenza-like illness patient report data. The authors also bring to bear a graph-based data mining technique to detect anomalies among flu blogs connected by publisher type, links, and user-tags.
Publication Title:
International Journal of Environmental Research and Public Health
Volume:
7
Issue:
2
Page Start:
596
Page End:
615
Peer Reviewed:
Yes
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Corley, Courtney; Cook, Diane J., 1963-; Mikler, Armin R. & Singh, Karan P.Text and Structural Data Mining of Influenza Mentions in Web and Social Media,
article,
February 22, 2010;
[Basel, Switzerland].
(https://digital.library.unt.edu/ark:/67531/metadc111288/:
accessed April 19, 2024),
University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu;
crediting UNT College of Engineering.
