From the Gray Matter blog at the New York Times:
Many important public health questions are difficult and costly to answer. What kind of risks do highly localized sources of pollution, like dry cleaners that use volatile chemicals, pose to the health of nearby residents? Are people with many friends healthier, or do those friendships increase the likelihood of infectious disease? Do frequent visits to public spaces like bars, gyms and restaurants affect a person’s health?
Researchers have been striving for generations to answer such questions, using health surveys of samples of individuals and computational studies of simulated populations. Now, however, the rise of social media and the burgeoning field of data science provide powerful tools to find high-precision, real-world answers with little cost or effort.
The millions of people posting to sites like Twitter and Facebook can be viewed as a vast organic sensor network, providing a real-time stream of data about the social, biological and physical worlds. While people use social media to build and maintain their social ties, the “data exhaust” of their postings can be analyzed to provide an enormous range of information at a population scale.
For example, my research group at the University of Rochester has analyzed Twitter postings from millions of cellphone users in New York City to develop a system to monitor food-poisoning outbreaks at restaurants.
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