An analysis of data mined from Twitter could be useful in locating and preventing HIV outbreaks, according to researchers at the University of California, Los Angeles.
The UCLA researchers analyzed 550 million tweets from between May 26, 2012, and Dec. 9, 2012, using an algorithm to determine those tweets that suggested high-risk behavior that could lead to HIV infection. The researchers then plotted the tweets' location of origin and compared the mappings to geographical distributions of HIV cases to see if a statistical relationship existed.
Researchers found a significant correlation between tweets expressing high-risk behavior and counties with high numbers of reported HIV cases. The results suggest the feasibility of using big data collected from social media channels to detect where HIV outbreaks and drug use occurs.
"Ultimately, these methods suggest that we can use 'big data' from social media for remote monitoring and surveillance of HIV risk behaviors and potential outbreaks," said Sean Young, assistant professor of family medicine at the David Geffen School of Medicine at UCLA and co-director of the Center for Digital Behavior at UCLA, in a news release.
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