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 ...

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

When researchers working on developing a machine learning-based tool for detecting fake news realized there wasn’t enough data to train their algorithms, they did the only rational thing: They ...

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

These are then fed into a machine learning-based classifier, which is able to distinguish patterns of language, vocabulary and semantics of fake and real news, and automatically infer whether the ...

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 ...

Efforts to detect fake news are not as advanced as they would appear, given that the best practices so far rely on pattern detection that can itself be exploited by malicious actors, according to ...