Mapping Where the Kids Are Drinking on Social Media

Using social media in scientific studies is fraught. Only a certain (younger, more minority-heavy) demographic uses Twitter, for example, and social media posts only capture the behaviors of people who, well, report their behaviors on social media. Still, social media data has shown up in a number of studies since the mid-2000s, including inquiries into wide-ranging public health issues: depression, the spread of influenza, food poisoning. So why not drinking behaviors?

A team of computer science researchers from the University of Rochester have done just that, aggregating geotagged tweets about alcohol consumption using machine learning techniques—basically, algorithms that identify patterns in data, like repeated tweets of “wOoHoO #beer!!1!” The researchers also had an assist from the real humans behind Amazon’s Mechanical Turk, which pays people to do simple, repetitive, and easily-crowdsourced tasks (like identifying whether a social media post is really about drinking). Together, the machines and people flagged posts with mentions of “wine,” “drank,” “vodka,” “pong,” and “hammered”—among other delectable phrases.