In 2019, Facebook took down on average close to 2 billion fake accounts per quarter. Fraudsters use these fake accounts to spread spam, phishing links, or malware. It’s a lucrative business that ...

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 ...

Binghamton University's School of Management (SOM) has conducted research that proposes solutions to combat the spread of fake news using a combination of machine learning and blockchain technology.

With so much misinformation spreading in social media, Rice University researchers led by computer scientist Anshumali Shrivastava developed a method using machine learning (ML) to prevent the ...

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 ...

People are inundated with info every single day.Each minute, there are 98,000 tweets, 160 million emails sent, and 600 videos uploaded to YouTube. Politicians. Marketers. News outlets.

That approach to detecting fake news has come to be referred to as the "provenance" approach, meaning it tells fake from real by looking at where the generation of words comes from, human or machine.