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Researchers identify seven types of fake news aiding better detection

Penn State News – “To help people spot fake news, or create technology that can automatically detect misleading content, scholars first need to know exactly what fake news is, according to a team of Penn State researchers. However, they add, that’s not as simple as it sounds. “There is a real crisis in our cultural understanding of the term ‘fake news,’ so much so that several scholars have actively moved away from that label because it’s so muddy, confusing and weaponized by certain partisan sources,” said S. Shyam Sundar, James P. Jimirro Professor of Media Effects and co-director of the Media Effects Research Laboratory in the Donald P. Bellisario College of Communications.

In a study, researchers narrowed down myriad examples of fake news to seven basic categories, which include false news, polarized content, satire, misreporting, commentary, persuasive information and citizen journalism. The researchers also contrasted those types of content with real news and report their findings in the current issue of American Behavioral Scientist… [h/t Pete Weiss]

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