Machine learning-based models, especially natural language processing, are becoming more sophisticated and effective in detecting fake news ...

A machine learning system aims to determine if a news outlet is accurate or biased.

Detecting fake news, at its source Date: October 5, 2018 Source: Massachusetts Institute of Technology, CSAIL Summary: A machine learning system aims to determine if a news outlet is accurate or ...

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 ...

A fake news article could be produced by selectively editing facts, including people’s names, dates or statistics. An article could also be completely fabricated with made-up events or people.

Spotting fake news Our research identifies linguistic characteristics to detect fake news using machine learning and natural language processing technology.

The freedom to share and access news online comes with the risk of falling into the trap of so-called fake news, and the development of neural networks and machine learning has only exacerbated the ...

Bespoke fraud ML models are powered by algorithms that learn from historical data, picking up on behaviors and characteristics commonly associated with fraud.