(Credit: wavebreakmedia/Shutterstock) Drunk tweets, long considered an unfortunate, yet ubiquitous, byproduct of the social media age, have finally been put to good use. With the help of a machine-learning algorithm, researchers from the University of Rochester cross-referenced tweets mentioning alcohol consumption with geo-tagging information to broadly analyze human drinking behavior. They were able to estimate where and when people imbibed, and, to a limited extent, how they behaved under the influence. The experiment is more than a social critique — the algorithm helps researchers spot drinking patterns that could inform public health decisions, and could be applied to a range of other human behaviors.
To begin with, the researchers sorted through a selection of tweets from both New York City and rural New York with the help of Amazon's Mechanical Turk. Users identified tweets related to drinking and picked out keywords, such as "drunk," "vodka" and "get wasted," to train ...
