Flu Detector - Tracking Epidemics on Twitter

  • Vasileios Lampos
  • Tijl De Bie
  • Nello Cristianini
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6323)


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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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Vasileios Lampos
    • 1
  • Tijl De Bie
    • 1
  • Nello Cristianini
    • 1
  1. 1.Intelligent Systems LaboratoryUniversity of BristolUK

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