Flu detector - Tracking Epidemics on Twitter

V Lampos, Tijl De Bie, Nello Cristianini

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

159 Citations (Scopus)


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.
Translated title of the contributionFlu detector - Tracking Epidemics on Twitter
Original languageEnglish
Title of host publicationECML PKDD 2010
Pages599 - 602
Number of pages4
Publication statusPublished - 18 Aug 2010

Bibliographical note

Conference Proceedings/Title of Journal: Machine Learning and Knowledge Discovery in Databases European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010, Proceedings, Part III
Conference Organiser: José Luis Balcázar, Francesco Bonchi, Aristides Gionis and Michèle Sebag


Dive into the research topics of 'Flu detector - Tracking Epidemics on Twitter'. Together they form a unique fingerprint.

Cite this