At the heart of every bot-detection tool is a human's gut feeling—and all the messiness that comes with it.
There’s a mystical quality in the way Yang speaks about how the team trains the Random Forest, the supervised machine-learning algorithm at the core of Botometer. “When I ask other people to label accounts, I don’t give them too many specific directions,” Yang says. “There are signals in bots that are hard to describe but that humans notice.” In other words, the Botometer team is trying to bake in some of the human instincts that allow people to detect who’s human and who’s not.
The tools are also evolving. The Botometer you can use today is the fourth version of the tool, according to Menczer, and it’s trained using new data sets that account for changes in bot behavior. “We add new data sets, we add new features. Sometimes we remove features that we don’t think are as useful anymore,” he says.
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