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

Courtney Corley,Karan Singh,Diane Cook,Armin Mikler

doi:10.3390/ijerph7020596

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.

Highlights

Influenza diagnosis based solely on the presentation of symptoms is limited as these symptoms may be associated with many other diseases
To prove our hypothesis that a correlation exists between Centers for Disease Control and Prevention (CDC) ILINet reports and mined Web and social media (WSM) FC-post frequency, Pearson's correlation statistic is evaluated between the two data series
We comprehensively evaluate blog posts containing influenza topic keywords through text, link, and structural data mining

Summary

Introduction

Influenza diagnosis based solely on the presentation of symptoms is limited as these symptoms may be associated with many other diseases. Serologic and antigen tests require that a patient with influenza-like illness (ILI) be examined by a physician who can either conduct a rapid diagnostic test or take blood samples in a laboratory testing. This suggests that many cases of influenza remain undiagnosed. While the presence of influenza in an individual can be confirmed through specific diagnostic tests, the influenza prevalence in the population at any given time is unknown and can only be estimated In the past, such estimates have relied solely on the extrapolation of diagnosed cases, making it difficult to identify the various phases of seasonal influenza or to identify a more serious manifestation of a flu epidemic. A well-defined response strategy to an outbreak may make use of WSM to reduce population and human impact of the disease

Methods

Results

Conclusion