This research program focuses on the potential of AI, in particular machine learning and natural language processing, to identify fake news stories.

This leads to the question: How can fake news be detected? The good news is that algorithms designed to distinguish between human- and AI-generated content have been developed.

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 ...

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 ...

Detecting misinformation Detecting misinformation can be done by a combination of algorithms, machine-learning models, artificial intelligence, and humans.

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

Detecting misinformation Detecting misinformation can be done by a combination of algorithms, machine-learning models and humans. An important question is who is responsible for controlling, if not ...

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 ...

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