UCLA researchers conducted a study that looked at 550 million geo-located tweets from May to December of 2012. They created an algorithm to scan tweets that suggested risky behavior, which included terms like "sex" or "get high."

From their report in the journal Preventative Medicine:

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.

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