Machine Learning may help debunk fake news

To combat fake news, a team of researchers has devised a new Machine Learning-driven program that will help identify how true a particular piece of information is. The researchers from the Massachusetts Institute of Technology and the Qatar Computing Research Institute took data from Media Bias/Fact Check, a website with human fact-checkers who analysed the accuracy and biases of more than 2,000 news sites. The team then fed that data to an ML algorithm called a Support Vector Machine classifier, and programmed it to classify news sites. The team determined that the most reliable way to detect both fake news and biased reporting was to look at the common linguistic features across the source’s stories, including sentiment, complexity and structure. For example, fake news outlets were found to be more likely to use language that is hyperbolic, subjective and emotional.

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