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People are bad at spotting fake news. Can computer programs do better?

There’s just too much misinformation online for human fact-checkers to catch it all

By
1:30pm, July 26, 2018
fake news detector illustration

DECEPTION MONITORS  Researchers are building online algorithms to check the veracity of online news. 

Scrolling through a news feed often feels like playing Two Truths and a Lie.

Some falsehoods are easy to spot. Like reports that First Lady Melania Trump wanted an exorcist to cleanse the White House of Obama-era demons, or that an Ohio school principal was arrested for defecating in front of a student assembly. In other cases, fiction blends a little too well with fact. Was CNN really raided by the Federal Communications Commission? Did cops actually uncover a meth lab inside an Alabama Walmart? No and no. But anyone scrolling through a slew of stories could easily be fooled.

We live in a golden age of misinformation. On Twitter, falsehoods spread further and faster than the truth (SN: 3/31/18, p. 14). In the run-up to the 2016 U.S. presidential election, the most popular bogus articles got more Facebook shares, reactions and comments than the top real news,

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