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Machine Learning, Blockchain Technology Could Help Counter Spread of Fake News

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Binghamton University's Thi Tran said traceability is one of the nice features of blockchain, because it can identify and classify sources of misinformation to help with recognizing the patterns.

Credit: The Nation (Thailand)

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 is likely to do the most public harm, according to new research from Binghamton University, State University of New York.

The research led by Thi Tran, assistant professor of management information systems at Binghamton University's School of Management, expands on existing studies by offering tools for recognizing patterns in misinformation and helping content creators zero in the worst offenders.

"I hope this research helps us educate more people about being aware of the patterns," Tran said, "so they know when to verify something before sharing it and are more alert to mismatches between the headline and the content itself, which would keep the misinformation from spreading unintentionally."

Tran's research proposed machine learning systems -- a branch of artificial intelligence (AI) and computer science that uses data and algorithms to imitate the way humans learn while gradually improving its accuracy -- to help determine the scale to which content could cause the most harm to its audience.

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