Abstract
The explosive use of social media sites presents a unique opportunity for developing alternative methods for understanding the health of the public. The emerging field of 'digital epidemiology' has been shown to detect outbreaks of influenza-like illness 1-2 weeks in advance of traditional surveillance methods. However, behaviors that lead to increased risk for disease have not yet been studied in this manner. We present a surveillance methodology to help sift through the vast volumes of social media data to detect behaviors and determinants of health contributing to both disease transmission and chronic illness.
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