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