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Predicting Disease Prevalence In Real Time Using Twitter

Adam Sadilek from Fount.in and his co-developer from the University of Rochester created a tool that tracks diseases based on the location of Twitter messages and keywords (e.g., ‘I feel sick’, ‘I have a sore throat’ or ‘My body aches’).

According to the developers, previous methods such as Google Flu Trends and government data entail time lags from days to years.

Here is an example that looks at the health of New Yorkers with the web application at Fount.in.

You see a heatmap visualization of the prevalence of flu in New York City, as observed through public Twitter data. The more red an area is, the more people are afflicted by flu at that location.

Fount.in also tracks the movement of Twitter users, the interactions of sampled cliques of friends, and the application can help to understand the public sentiment around a topic, product, or brand.

Very interesting! There is a lot for us to learn from in this realm…


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