Fake news articles contained significantly higher levels of negative sentiment, including emotions such as fear, anger, ...

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 ...

Our fake news detector is built based on linguistic characteristics extracted from a large body of news articles. It takes a piece of text and shows how similar it is to the fake news and real ...

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 ...

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 ...