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 ...

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.

Designers of fake news websites could figure out what algorithms are looking for, and adjust how their content is created to get around those systems set up to prevent their circulation. Lee says 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 ...

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 ...

Adversarial machine learning is the process of creating malicious or misinforming content that can slip past detection programs.