Fake News Detector Algorithm Works Better Than a Human

EurekAlert! Public Release: 8/21/18

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.

Rada Mihalcea, the U-M computer science and engineering professor behind the project, said an automated solution could be an important tool for sites that are struggling to deal with an onslaught of fake news stories, often created to generate clicks or to manipulate public opinion.

Read more of this article, published on www.eurekalert.org, by clicking on the title link.