It may be possible to predict sexual risk and drug use behaviours by monitoring tweets, mapping where those messages come from and linking them with data on the geographical distribution of HIV cases. (Agencies)
"This is the first such study. We can use 'big data' from social media for remote monitoring and surveillance of HIV risk behaviours and potential outbreaks," said Sean Young, assistant professor of family medicine at University of California, Los Angeles.
For the study, researchers collected more than 550 million tweets and created an algorithm to find words and phrases in them suggesting drug use or potentially risky behaviours, 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.
The algorithm captured 8,538 tweets indicating sexually risky behaviour and 1,342 suggesting stimulant drug use. When the researchers linked the tweets to data on HIV cases, they found a significant relationship between those indicating risky behaviour and counties where the highest numbers of HIV cases were reported.
Based on this study, the researchers concluded that it is possible to collect 'big data' on real-time social media like Twitter about sexual and drug use behaviours - create a map of where the tweets are occur and use this information to possibly predict where HIV cases and drug use occur.
The study was published in the journal Preventive Medicine.
It may be possible to predict sexual risk and drug use behaviours by monitoring tweets, mapping where those messages come from and linking them with data on the geographical distribution of HIV cases.