Researchers found that integrating emotional features, particularly negative emotions, into machine learning models enhances the accuracy of fake news detection on social media platforms.

Researchers proposed solutions to combat the spread of fake news using a combination of machine learning and blockchain technology.

Rice University researchers integrated machine learning to prevent the spread of misinformation online.

His research on effect-oriented fake news detection using Machine Learning was one among the AWSAR-2019 award winners for the best popular science stories, instituted by the Department of Science ...

As with so many of our modern problems, artificial intelligence is now on the job helping to fight false news. Logically is one company that uses artificial intelligence to provide fact-checking ...

That approach to detecting fake news has come to be referred to as the "provenance" approach, meaning it tells fake from real by looking at where the generation of words comes from, human or machine.