Twitter ‘Big Data’ Used to Monitor HIV Risk, Study Shows

March 7, 2014
A new UCLA-led study shows that real-time social media, such as Twitter, could be used to track HIV incidence and drug-related behaviors with the aim of detecting and potentially preventing outbreaks.

A new UCLA-led study shows that real-time social media, such as Twitter, could be used to track HIV incidence and drug-related behaviors with the aim of detecting and potentially preventing outbreaks.

The study, published in the peer-reviewed journal Preventive Medicine, suggests it may be possible to predict sexual risk and drug use behaviors by monitoring tweets, mapping where those messages come from, and linking them with data on the geographical distribution of HIV cases. The use of various drugs had been associated in previous studies with HIV sexual risk behaviors and transmission of infectious disease.

For the study, researchers collected more than 550 million tweets between May 26 and Dec. 9, 2012, and created an algorithm to find words and phrases in them suggesting drug use or potentially risky behaviors, such as "sex" or "get high." They then plotted those tweets on a map to discover where they originated, running statistical models to see if these were areas where HIV cases had been reported.

"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," 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, said in a UCLA news release.

Founded by Young, the new interdisciplinary center brings together academic researchers and private sector companies to study how social media and mobile technologies can be used to predict and change behavior.

Other studies have examined how Twitter can be used to predict outbreaks of infections like influenza, said Young, “but this is the first to suggest that Twitter can be used to predict people's health-related behaviors and as a method for monitoring HIV risk behaviors and drug use,” he said.

The algorithm captured 8,538 tweets indicating sexually risky behavior and 1,342 suggesting stimulant drug use. The geographical data on HIV cases to which researchers linked the tweets came from AIDSVu.org, an interactive online map that illustrates the prevalence of HIV in the U.S.; this mapping data was from 2009.

When the researchers linked the tweets to data on HIV cases, they found a significant relationship between those indicating risky behavior and counties where the highest numbers of HIV cases were reported. 

Based on this study, the researchers conclude that it is possible to collect "big data" on real-time social media like Twitter about sexual and drug use behaviors, create a map of where the tweets are occur, and use this information to understand and possibly predict where HIV cases and drug use occur.

UCLA has not been averse to using social media in clinical settings. Last year, a team of UCLA Health System brain specialists implanted a brain pacemaker in a 39-year-old man. It was the 500th such procedure the team had completed, but the first time the group had invited followers to observe the procedure on Twitter. Updates with Instagram photos and short video clips were posted using the hashtag #UCLAORLive.

Read the source article at Home / UCLA Newsroom

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