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The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.

Tracking the flu pandemic by monitoring the social web

Lampos, Vasileios, Cristianini, Nello·2010·2010 2nd International Workshop on Cognitive Information Processing

Abstract

Tracking the spread of an epidemic disease like seasonal or pandemic influenza is an important task that can reduce its impact and help authorities plan their response. In particular, early detection and geolocation of an outbreak are important aspects of this monitoring activity. Various methods are routinely employed for this monitoring, such as counting the consultation rates of general practitioners. We report on a monitoring tool to measure the prevalence of disease in a population by analysing the contents of social networking tools, such as Twitter. Our method is based on the analysis of hundreds of thousands of tweets per day, searching for symptom-related statements, and turning statistical information into a flu-score. We have tested it in the United Kingdom for 24 weeks during the H1N1 flu pandemic. We compare our flu-score with data from the Health Protection Agency, obtaining on average a statistically significant linear correlation which is greater than 95%. This method uses completely independent data to that commonly used for these purposes, and can be used at close time intervals, hence providing inexpensive and timely information about the state of an epidemic.

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Metadata

Authors
Lampos, V., & Cristianini, N.
Venue
2010 2nd International Workshop on Cognitive Information Processing
Publisher
IEEE
Published
2010-06
Pages
411-416
OpenAlex
W2141701578
Cited by
304
References
12
FWCI
157.61
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Tracking the flu pandemic by monitoring the social web. https://app.cochat.ai/papers/10.1109/cip.2010.5604088
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Lampos, V., & Cristianini, N. (2010). Tracking the flu pandemic by monitoring the social web. 2010 2nd International Workshop on Cognitive Information Processing. https://doi.org/10.1109/cip.2010.5604088

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