How Twitter Can Predict When Individuals Will Get Sick

Sadilek and his team analysed 4.4 million tweets tagged with GPS location data from over 630,000 users in the New York City area over one month in 2010. They trained a machine-learning algorithm to tell the difference between tweets by healthy people – who might say something like “I am so sick of this traffic!” – and someone who is actually sick and showing signs of the flu. The video shows a heat map of flu occurrence over the course of one day, based on their findings.

http://gizmodo.com/5929196/how-twitter-can-predict-when-individuals-will-get-sick

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