#wheezing: A Content Analysis of Asthma-Related Tweets


Recently, a growing number of studies have made use of Twitter to track the spread of infectious disease. These investigations show that there are reliable spikes in traffic related to keywords associated with the spread of infectious diseases like Influenza [1], as well as other Syndromes [2]. However, little research has been done using Social Media to monitor chronic conditions like Asthma, which do not spread from sufferer to sufferer. We therefore test the feasibility of using Twitter for Asthma surveillance, using techniques from NLP and machine learning to achieve a deeper understanding of what users Tweet about Asthma, rather than relying only on keyword search.


We present a Content Analysis project using Natural Language Processing to aid in Twitter-based syndromic surveillance of Asthma

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Event/Publication Date: 
December, 2012

January 19, 2018

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Email: syndromic@cste.org


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