ANN ARBOR—An algorithm-based system that identifies telltale linguistic cues in fake news stories could provide news aggregator and social media sites like Google News with a new weapon in the fight against misinformation.
The University of Michigan researchers who developed the system have demonstrated that it’s comparable to and sometimes better than humans at correctly identifying fake news stories.
In a recent study, it successfully found fakes up to 76 percent of the time, compared to a human success rate of 70 percent. In addition, their linguistic analysis approach could be used to identify fake news articles that are too new to be debunked by cross-referencing their facts with other stories.
Source: Fake news detector algorithm works better than a human | University of Michigan News