Text and Structural Data Mining of Influenza Mentions in Web and Social Media
AbstractText 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.
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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.
Corley CD, Cook DJ, Mikler AR, Singh KP. Text and Structural Data Mining of Influenza Mentions in Web and Social Media. International Journal of Environmental Research and Public Health. 2010; 7(2):596-615.Chicago/Turabian Style
Corley, Courtney D.; Cook, Diane J.; Mikler, Armin R.; Singh, Karan P. 2010. "Text and Structural Data Mining of Influenza Mentions in Web and Social Media." Int. J. Environ. Res. Public Health 7, no. 2: 596-615.