Algorithms can help stomp out fake news

This week, a BuzzFeed survey found that three in four American adults who see fake-news headlines headlines believe them. It’s not hard to see why: A website peddling made-up news stories can easily look nearly as polished as The New York Times, and it’s impossible to keep up with the sheer volume of information published online every minute. And when people believe fake news stories, real things happen—like an assault rifle-wielding man visiting a D.C. pizza joint because he appeared to think the restaurant was involved in a debunked Clinton-centered pedophilia conspiracy.

Fact checkers need a hand if they’re going to catch up with the pace and breadth of the material shared every day on Facebook, Twitter, and elsewhere around the internet. As soon as next year, they might get that help—in the form of computer algorithms and artificial intelligence.

There are several ways to determine whether a story is true or not, says Carlos Castillo, a data scientist at a research center in Spain called Eurecat. The simplest is to just to consider the source: If the story was published in a prestigious newspaper, for example, or by a decorated journalist, it’s probably more likely to be trustworthy. Another method is to study the way a story is shared on social media: the kinds of words used to describe it, the sorts of users who post it, and the way people respond to it. And a third method is to examine the story itself, by analyzing its internal logic, combing it for claims, and checking those claims against known facts.

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