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 ...

Researchers proposed solutions to combat the spread of fake news using a combination of machine learning and blockchain technology.

Rice University researchers integrated machine learning to prevent the spread of misinformation online.

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 ...

An artificial intelligence course has been launched that includes two projects focused on using AI to detect and combat fake news articles.

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.

Currently, there are basically two types of tools to detect fake news. Firstly, there are automatic ones based on machine learning, of which (currently) only a few prototypes are in existence.