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

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

The language gives it away: How an algorithm can help us detect fake news Researchers are developing an algorithm that can distinguish between real and fake news articles.

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 ...

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

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 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 ...

Adversarial machine learning is the process of creating malicious or misinforming content that can slip past detection programs.

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 ...

Astroscreen is a startup that uses machine learning and disinformation analysts to detect social media manipulation. It has now secured $1 million in initial funding to progress its technology.