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

Have you ever read something online and shared it among your networks, only to find out it was false? As a software engineer and computational linguist who spends most of her work and even leisure ...

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 ...

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.

Fake news is a problem. This is inarguable. However, exactly how to identify and deal with it is a challenge with no really good solution. Google, Facebook and other tech giants are struggling with ...

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

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.

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

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