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

For an AI system detecting fake news, to be super accurate, the hits need to be really high (say 90%) and so the misses will be very low (say 10%), and the false alarms need to stay low (say 10% ...

In fact, a Pew Research Center survey found that 10% of respondents admitted to sharing a news story online that they knew was fake, while 49% had shared news that they later found to be false.

Fabula AI is using social spread to spot ‘fake news’ Natural language limitations Naturally Grover is best at detecting its own fake articles, since in a way the agent knows its own processes.

The conundrum of fake news detection, say MIT researchers, is that valid, factually correct writing can come from automatic, machine-generated text, ...

We sought to build upon and complement Pennycook’s work, by assessing fake news detection in a sample of UK participants across a range of news topics including health, ...