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.

Currently, there are basically two types of tools to detect fake news. Firstly, there are automatic ones based on machine learning, of which (currently) only a few prototypes are in existence.

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 ...

But there’s hope that the use of deep learning can help automate some of the steps of the fake news detection pipeline and augment the capabilities of human fact-checkers.

Most fake content requires a human to detect and report it, new technology could change this.

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 ...