Using Twitter To Track Pandemics?
A new study raises some interesting possibilities for the use of social media to track and predict public health threats:
Any person who’s feeling a little under the weather knows that some of the best medicine is sympathy. And where better to find tons of sympathy than from your social media group. Type in “#feelingsick” to Twitter to see what I mean.
Even if no one responded to your sympathy fishing, don’t worry, Adam Sadilek and his colleagues at theUniversity of Rochester in New York have been paying attention.
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.
This raises some intriguing ideas, including the possibility that monitoring social networks in this manner could give public health officials advance warning of a disease outbreak. It’s not perfect, of course, but combined with data from other sources such as doctor’s offices and Emergency Room’s, it could assist medical officials in being able to address a pandemic at a faster pace than they might have been able to do in the past.
“Emergency Rooms” is correct. Sorry, I’m moody.