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Monitoring Influenza Trends though Mining Social Media. By Courtney D Corley, Armin R Mikler , Karan P Singh, and Diane J Cook . Jedsada Chartree 02/07/2011. Outline. Introduction Motivation Methodology Results Conclusion. Introduction. - PowerPoint PPT Presentation
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Monitoring Influenza Trends though Mining Social Media
By Courtney D Corley, Armin R Mikler,Karan P Singh, and Diane J Cook
Jedsada Chartree02/07/2011
Outline
• Introduction• Motivation• Methodology• Results• Conclusion
Introduction
• 1. Influenza (Flu) is an infectious disease caused by influenza viruses, that affects birds and mammals.
Source: http://en.wikipedia.org/wiki/Influenza
Introduction
• Influenza Symptoms - Chills, fever, sore throat, muscle pains, severe
headache, coughing, weakness/fatigue
Source: http://en.wikipedia.org/wiki/Influenza
• Influenza Transmission - Air (coughs/sneezes) - Direct contact
Introduction
Source: http://www.google.org/flutrends/us/#US
Influenza season in the US
Introduction
• 2. Social Media - Media for social interaction - The use of web-based and mobile technology to
turn communication into interactive dialogue.
Introduction
Social Media: Blogger, WordPress, Google Buzz, Twitter, Facebook, Hi5, MySpace
Source: http://www.webseoanalytics.com/blog/social-media-best-practices-for-businesses/
Motivation
• Difficulty of identifying the Influenza - Patients with Influenza-like-illness (ILI) have to be
examined by physicians.• Web and Social Media (WSM) provide a resource
increases in ILI.
Methodology
• Data - Spinn3r: a web service for indexing all blogs connected as community/social network . - 44 million posts from 1-August to 30-September, 2008
Methodology/Results
Actual and Average Blog-World Posts per Day of Week
Methodology/Results
Methodology/Results
Autocorrelation Function (ACF) is the similarity between observations as a function of the time separation between them.
Methodology/ResultsFC-post trends
Methodology/ResultsBlog Category occurrence per Month
Response Strategy in “Flu” Blog Communities
• Identify WSM Influenza-related communities that share flu-postings which could disseminate information.
- Bloggers: first response (link analysis) - Readers
Response Strategy in “Flu” Blog Communities
1. Closeness: Finding the average shortest parts from each actor and all reachable actors.
2. Betweenness centrality: A blog is central if it lies between other blogs.
3. Google’s PageRank: A numerical weighting to each website.
Response Strategy in “Flu” Blog Communities
Conclusion• Strong correlation between FC-Posts per week and CDC• Web and social media provide resources to detect increases in
ILI• WSM Influenza-related communities could share information
in the case of flu outbreak.
References• C. Corley, A. Mikler, K. Singh, and D. Cook. 2009. Monitoring influenza trends
through mining social media. International Conference on Bioinformatics and Computational Biology (BIOCOMP09).