Text and Structural Data Mining of Influenza Mentions in Web and Social Media

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This article discusses text and structural data mining of influenza mentions in web and social media.

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20 p.

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Corley, Courtney; Cook, Diane J., 1963-; Mikler, Armin R. & Singh, Karan P. February 22, 2010.

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This article is part of the collection entitled: UNT Scholarly Works and was provided by the UNT College of Engineering to the UNT Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 465 times. More information about this article can be viewed below.

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This article discusses text and structural data mining of influenza mentions in web and social media.

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20 p.

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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.

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  • International Journal of Environmental Research and Public Health, 2010, Basel: Multidisciplinary Digital Publishing Institute (MDPI), pp. 596-615

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  • Publication Title: International Journal of Environmental Research and Public Health
  • Volume: 7
  • Page Start: 596
  • Page End: 615
  • Peer Reviewed: Yes

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  • February 22, 2010

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  • Nov. 2, 2012, 1:21 p.m.

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  • Aug. 13, 2020, 3:10 p.m.

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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 September 28, 2023), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT College of Engineering.

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