Researchers at Rutgers University have found a major flaw in the way that algorithms designed to detect “fake news” evaluate the credibility of online news stories. Most of these algorithms rely on a credibility score for the “source” of the article, rather than assessing the credibility of each individual article, the researchers said. “It is not the case that all news articles published by sources labeled ‘credible’ (e.g., The New York Times) are accurate, nor is it the case that every article published by sources labeled ‘noncredible’ publications are ‘fake news,'” said Vivek K. Singh, an associate professor at the Rutgers School of Communication and Information and coauthor of the study “Misinformation Detection Algorithms and Fairness Across Political Ideologies: The Impact of Article Level Labeling” published on OSFHome. To read the full story.