Monitoring Influenza Trends though Mining Social Media

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).