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

被引：139

作者：

Corley, Courtney D. ^{[1
]}

Cook, Diane J. ^{[2
]}

Mikler, Armin R. ^{[3
]}

Singh, Karan P. ^{[4
]}

机构：

[1] Pacific NW Natl Lab, Richland, WA 99352 USA

[2] Washington State Univ, Sch Elect Engn & Comp Sci, Pullman, WA 99164 USA

[3] Univ N Texas, Dept Comp Sci & Engn, Denton, TX 76203 USA

[4] Univ N Texas, Hlth Sci Ctr, Dept Biostat, Ft Worth, TX 76107 USA

来源：

INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH | 2010年 / 7卷 / 02期

基金：

美国国家科学基金会;

关键词：

disease surveillance; public health epidemiology; health informatics; graph-based data mining; web and social media; social network analysis;

D O I：

10.3390/ijerph7020596

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

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.

引用

页码：596 / 615

页数：20

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