monitoring influenza trends though mining social media
DESCRIPTION
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 PresentationTRANSCRIPT
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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
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Outline
• Introduction• Motivation• Methodology• Results• Conclusion
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Introduction
• 1. Influenza (Flu) is an infectious disease caused by influenza viruses, that affects birds and mammals.
Source: http://en.wikipedia.org/wiki/Influenza
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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
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Introduction
Source: http://www.google.org/flutrends/us/#US
Influenza season in the US
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Introduction
• 2. Social Media - Media for social interaction - The use of web-based and mobile technology to
turn communication into interactive dialogue.
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Introduction
Social Media: Blogger, WordPress, Google Buzz, Twitter, Facebook, Hi5, MySpace
Source: http://www.webseoanalytics.com/blog/social-media-best-practices-for-businesses/
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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.
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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
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Methodology/Results
Actual and Average Blog-World Posts per Day of Week
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Methodology/Results
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Methodology/Results
Autocorrelation Function (ACF) is the similarity between observations as a function of the time separation between them.
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Methodology/ResultsFC-post trends
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Methodology/ResultsBlog Category occurrence per Month
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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
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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.
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Response Strategy in “Flu” Blog Communities
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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.
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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).