In recent years, Johns Hopkins researchers have shown that tweets can help trace nationwide trends in flu outbreaks. Now, in a new study, a team from Johns Hopkins and George Washington universities has drilled even deeper, probing flu-related tweets from a single bustling metropolis: New York City. Twitter data, the team concluded, can accurately gauge the spread of flu at the local level, too.
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Sifting through social media messages has become a popular way to track when and where flu cases occur, but a key hurdle hampers the process: how to identify flu-infection tweets. Some tweets are posted by people who have been sick with the virus, while others come from folks who are merely talking about the illness. If you are tracking actual flu cases, such conversations about the flu in general can skew the results. To address this problem, Johns Hopkins computer scientists and researchers in the School of Medicine have developed a new tweet-screening method that not only delivers real-time data on flu cases, but also filters out online chatter that is not linked to actual flu infections.