PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Flu Detector - Tracking Epidemics on Twitter
Vasileios Lampos, Tijl De Bie and Nello Cristianini
In: ECML PKDD 2010, 20-24 Sep 2010, Barcelona, Spain.

Abstract

We present an automated tool with a web interface for tracking the prevalence of Influenza-like Illness (ILI) in several regions of the United Kingdom using the contents of Twitter's microblogging service. Our data is comprised by a daily average of approximately 200,000 geolocated tweets collected by targeting 49 urban centres in the UK for a time period of 40 weeks. Official ILI rates from the Health Protection Agency (HPA) form our ground truth. Bolasso, the bootstrapped version of LASSO, is applied in order to extract a consistent set of features, which are then used for learning a regression model.

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EPrint Type:Conference or Workshop Item (Paper)
Additional Information:Flu Detector's website: http://geopatterns.enm.bris.ac.uk/epidemics/
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
Information Retrieval & Textual Information Access
ID Code:6979
Deposited By:Vasileios Lampos
Deposited On:20 July 2010