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Using 4.4 million tweets with GPS location from over 630,000 users in New York City, Sadilek and his team were able to predict when an individual would get sick with the flu and tweet about it up to eight days in advance of their first symptoms. Researchers found they could predict said results with 90 percent accuracy.
Similar to Google's Flu trends, which uses "flu" search trends to pinpoint where and how outbreaks are spreading, Sadilek's system uses an algorithm to differentiate between alternative definitions of the word 'sick.' For example, "My stomach is in revolt. Knew I shouldn't have licked that door knob. Think I'm sick," is different from "I'm so sick of ESPN's constant coverage of Tim Tebow."
Of course, Sadilek's system isn't an exhaustive crystal ball. Not everyone tweets about their symptoms and not everyone is on Twitter. But considering New York City has more Twitter users than any other city in the world, the Big Apple is as good as a place as any for this study.
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Wouldn't it be cool if one day our smartphones or social network accounts used a system like this to warn us if we're at risk of getting sick? Until then, make sure to get enough exercise and sleep your body needs to stay healthy. And if you do feel like you're coming down with something, I'm always fond of fighting off sickness by bolstering my immune system with the dynamic duo of Vitamin C and Raw Garlic. Plus, that combo keeps the vampires away.
Below is a heat-map visualization of the flu spreading across New York City over the course of one day.
Credit: Adam Sadilek