A proposed machine learning framework and expanded use of blockchain technology could help counter the spread of fake news by allowing content creators to focus on areas where the misinformation ...

The proposed machine learning framework, a division of artificial intelligence (AI), aims to utilize data and algorithms to identify signs of misinformation and enhance the detection process.

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 ...

Fake video and audio might once again be poised to corrupt the most basic ways in which people process reality—or what’s left of it. So far, deepfakes have been limited by two factors baked ...

Detecting misinformation. Detecting misinformation can be done by a combination of algorithms, machine-learning models and humans. An important question is who is responsible for controlling, if ...

Controlling the spread of fake news may, in some instances, be considered censorship and a threat to freedom of speech and expression. Even a human may have a hard time judging whether information ...