title: Text and structural data mining of influenza mentions in Web and social media.
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.
authors.affiliation: Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99352, USA. cook@eecs.wsu.edu
authors.forename: Courtney D
authors.initials: CD
authors.lastname: Corley
authors.forename: Diane J
authors.initials: DJ
authors.lastname: Cook
authors.forename: Armin R
authors.initials: AR
authors.lastname: Mikler
authors.forename: Karan P
authors.initials: KP
authors.lastname: Singh
mesh_terms: D006801:Humans; D007251:Influenza, Human; D016247:Information Storage and Retrieval; D020407:Internet; D011159:Population Surveillance; D012944:Social Support