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Int. J. Environ. Res. Public Health 2010, 7(2), 596-615; doi:10.3390/ijerph7020596
Article

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

1,* , 2
,
3
 and
4
1 Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99352, USA 2 School of Electrical Engineering and Computer Science, Washington State University, PO Box 642752 Pullman, Washington 99164, USA 3 Department of Computer Science and Engineering, University of North Texas, 1155 Union Circle #311366 Denton, TX 76203, USA 4 Department of Biostatistics, University of North Texas Health Science Center, 3500 Camp Bowie Blvd. Fort Worth, TX 76107, USA
* Author to whom correspondence should be addressed.
Received: 9 November 2009 / Accepted: 10 February 2010 / Published: 22 February 2010
(This article belongs to the Special Issue Public Health Informatics)
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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. We also bring to bear a graph-based data mining technique to detect anomalies among flu blogs connected by publisher type, links, and user-tags.
Keywords: disease surveillance; public health epidemiology; health informatics; graph-based data mining; web and social media; social network analysis disease surveillance; public health epidemiology; health informatics; graph-based data mining; web and social media; social network analysis
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).
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Corley, C.D.; Cook, D.J.; Mikler, A.R.; Singh, K.P. Text and Structural Data Mining of Influenza Mentions in Web and Social Media. Int. J. Environ. Res. Public Health 2010, 7, 596-615.

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