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 ...

An algorithm that can already detect fake news stories with 75 percent accuracy gets a boost from Snap Research.

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

False stories are now spreading 10 times faster than real news and the problem of fake news seriously threatens our society.

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 ...

This leads to the question: How can fake news be detected? The good news is that algorithms designed to distinguish between human- and AI-generated content have been developed.

Social networks could incorporate similar machine-learning algorithms that would warn users about dangerous or untrustworthy content.

How far does the world have to go to detect fake, computer-generated writing? Quite a bit farther, if recent research by MIT scientists is correct. Fake detection requires a lot of reliance by ...