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

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

About the study This study aimed to explore how emotional features, particularly negative emotions, could enhance the accuracy of machine learning models 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 ...

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 ...

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 ...

So, a machine learning system such as this one is by no means a magic bullet to the problem of fake or biased news, but it certainly presents us with a valuable tool to help manage the ongoing issue.

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.