Text and structural data mining of influenza mentions in web and social media

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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. © 2010 by the authors, Battelle Memorial Institute; licensee Molecular Diversity Preservation International.

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APA

Corley, C. D., Cook, D. J., Mikler, A. R., & Singh, K. P. (2010). Text and structural data mining of influenza mentions in web and social media. International Journal of Environmental Research and Public Health, 7(2), 596–615. https://doi.org/10.3390/ijerph7020596

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