Flu Detector - Tracking Epidemics on Twitter

Lecture notes in computer sciencePublished 1 January 2010

Vasileios Lampos, Tijl De Bie, Nello Cristianini

DOI10.1007/978-3-642-15939-8_42

Source URL

Citations255

SJR quartileQ2

SJR score0.35

SNIP0.55

TL;DR

An automated tool with a web interface for tracking the prevalence of Influenza-like Illness in several regions of the United Kingdom using the contents of Twitter's microblogging service.

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.

Keywords

Medicine

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