Add to ORKGWe 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
<div><p>Twitter has the potential to be a timely and cost-effective source of data for syndromic sur...
<div><p>Traditional methods for monitoring influenza are haphazard and lack fine-grained details reg...
Early detection of disease outbreaks is critical for disease spread control and management. In this ...
We present an automated tool with a web interface for tracking the prevalence of Influenza-like Illn...
Abstract. We present an automated tool with a web interface for track-ing the prevalence of Influenz...
We present a method for measuring the prevalence of disease in a population by analysing the content...
Flu Detector is a tool with a web interface for nowcasting the prevalence of Influenza-like Ill-ness...
Twitter - a social media platform - has gained phenomenal popularity among researchers who have expl...
Twitter has the potential to be a timely and cost-effective source of data for syndromic surveillanc...
Twitter has the potential to be a timely and cost-effective source of data for syndromic surveillanc...
<p>This figure shows the components of our system for estimating influenza prevalence from Twitter. ...
Modeling disease spread and distribution using social media data has become an increasingly popular ...
Abstract — Reducing the impact of seasonal influenza epidemics and other pandemics such as the H1N1 ...
Abstract — Reducing the impact of seasonal influenza epidemics and other pandemics such as the H1N1 ...
Traditional methods for monitoring influenza are haphazard and lack fine-grained details regarding t...
<div><p>Twitter has the potential to be a timely and cost-effective source of data for syndromic sur...
<div><p>Traditional methods for monitoring influenza are haphazard and lack fine-grained details reg...
Early detection of disease outbreaks is critical for disease spread control and management. In this ...
We present an automated tool with a web interface for tracking the prevalence of Influenza-like Illn...
Abstract. We present an automated tool with a web interface for track-ing the prevalence of Influenz...
We present a method for measuring the prevalence of disease in a population by analysing the content...
Flu Detector is a tool with a web interface for nowcasting the prevalence of Influenza-like Ill-ness...
Twitter - a social media platform - has gained phenomenal popularity among researchers who have expl...
Twitter has the potential to be a timely and cost-effective source of data for syndromic surveillanc...
Twitter has the potential to be a timely and cost-effective source of data for syndromic surveillanc...
<p>This figure shows the components of our system for estimating influenza prevalence from Twitter. ...
Modeling disease spread and distribution using social media data has become an increasingly popular ...
Abstract — Reducing the impact of seasonal influenza epidemics and other pandemics such as the H1N1 ...
Abstract — Reducing the impact of seasonal influenza epidemics and other pandemics such as the H1N1 ...
Traditional methods for monitoring influenza are haphazard and lack fine-grained details regarding t...
<div><p>Twitter has the potential to be a timely and cost-effective source of data for syndromic sur...
<div><p>Traditional methods for monitoring influenza are haphazard and lack fine-grained details reg...
Early detection of disease outbreaks is critical for disease spread control and management. In this ...