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

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 challenge for fake news detection comes with the democratization of news sources, and how easy modern technology makes sharing news articles in the age of social media.

They improved the 50-year old Bloom filter technology for scanning social media help social media network companies prevent the spread of fake news in their platforms.

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

When Mark Zuckerberg told Congress Facebook would use artificial intelligence to detect fake news posted on the social media site, he wasn’t particularly specific about what that meant. Given my ...

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 ...

By 2022, people in developed countries may see more fake news than accurate information. Artificial intelligence may be to blame – but could also help people sort out the truth from lies.