Using Twitter to Track the Flu: Researchers Find a Better Way to Screen the Tweets

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. Comparing their method, which is based on analysis of 5,000 publicly available tweets per minute, to other Twitter-based tracking tools, the Johns Hopkins researchers say their real-time results track more closely with government disease data that takes much longer to compile.

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Johns Hopkins University

Researchers:

Mark Dredze, Johns Hopkins University

David Broniatowski, Johns Hopkins University, Emergency Medicine, Post-Doc