Researchers at MIT’s Computer Science and Artificial Intelligence Lab (CSAIL) and the Qatar Computing Research Institute (QCRI) have demonstrated a new machine learning system that assesses the accuracy and/or biases of a source, such as a website, as a way to measure the quality of its content. The system works fairly quickly as well, researchers say, which would be an improvement over current anti-fake news methods, which include armies of human fact checkers running individual claims to the ground or AI machines that attempt to do the same. Whichever method is employed, false and misleading stories can circle the digital globe several times before fact checkers can catch up.
The MIT-Qatar system starts with the credibility of the source. “If a website has published fake news before, there’s a good chance they’ll do it again,” Ramy Baly, a post-doctoral MIT researcher and lead author of a paper about the system, said in MIT News. “By automatically scraping data about these sites, the hope is that our system can help figure out which ones are likely to do it in the first place.”
Researchers said the system can reliably assess a website’s trustworthiness based on about 150 articles, which they took from Media Bias/Fact Check (MBFC), whose human fact checkers rate more than 2,000 large and small news sites.
The most effective clues to bias were found in the consistent linguistic features of a site, including sentiment, complexity, and sentence structures, the researchers said. Purveyors of fake news, for instance, tended to employ hyperbolic, subjective, and emotional language more than other websites. They also found consistent linguistic features separating the political ends of the spectrum: left-leaning sites focus more on issues of harm and care, fairness, and reciprocity as opposed to markers such as loyalty, sanctity, and authority, researchers said.Fake news isn’t exactly new; the Founding Fathers had plenty of complaints about what they saw as the press peddling fiction as fact. But with the power of the internet, the emergence of AI techniques, and an apparent lowering of standards by political leaders and participants, its persistent presence threatens to overwhelm fact-based debate. If fake news is to be abated, it will be essential to identify it before it gains much traction.
