Stanford Computer Scientists Develop “Troll-Spotting Algorithm,” Explodes When Analyzing Breitbart.com

Using Breitbart as a test bed calls their results into question
Science • Views: 33,216

A group of Stanford computer scientists have developed an algorithm that supposedly can detect trolls by analyzing as few as five comments.

Today, Justin Cheng at Stanford University in California and a few pals say they have created just such a tool by analyzing the behavior of trolls on several well-known websites and creating an algorithm that can accurately spot them after as few as 10 posts. They say their technique should be of high practical importance to the people who maintain online communities.

Cheng and co study three online news communities: the general news site CNN.com, the political news site Breitbart.com, and the computer gaming site IGN.com.

On each of these sites, they have a list of users who have been banned for antisocial behavior, over 10,000 of them in total. They also have all of the messages posted by these users throughout their period of online activity. “Such individuals are clear instances of antisocial users, and constitute ‘ground truth’ in our analyses,” say Cheng and co.

OK, I just have to ask: how in the world can any algorithm pick out “trolls” at Breitbart “News?” Almost every commenter at that insane website is an antisocial lunatic. They don’t discourage antisocial nutcases — inciting them into a frenzy is their business model. If Breitbart “News” was one of their test beds I have to question the accuracy of this algorithm.

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