Flu Detector - Tracking Epidemics on Twitter

  • Vasileios Lampos
  • Tijl De Bie
  • Nello Cristianini
Conference paper

DOI: 10.1007/978-3-642-15939-8_42

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6323)
Cite this paper as:
Lampos V., De Bie T., Cristianini N. (2010) Flu Detector - Tracking Epidemics on Twitter. In: Balcázar J.L., Bonchi F., Gionis A., Sebag M. (eds) Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2010. Lecture Notes in Computer Science, vol 6323. Springer, Berlin, Heidelberg

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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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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