Media Bias/Fact Check

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Media Bias/Fact Check
Media Bias Fact Check wordmark.png
Founded2015; 6 years ago (2015)
HeadquartersGreensboro, North Carolina
OwnerDave Van Zandt[1]
URLmediabiasfactcheck.com Edit this at Wikidata
Current statusActive

Media Bias/Fact Check (MBFC) is an American website founded in 2015 by editor Dave Van Zandt.[1] The website has been described as an amateur effort to rate news media sources based on factual accuracy and political bias.[2]

Chart showing the degree of bias rating given to CNN

Sites are rated on a 0–10 scale by Van Zandt and his team using categories such as biased wording and headlines, factuality and sourcing, and story choices.[2]

The Columbia Journalism Review describes Media Bias/Fact Check as an amateur attempt at categorizing media bias and Van Zandt as an "armchair media analyst".[2] The Poynter Institute notes, "Media Bias/Fact Check is a widely cited source for news stories and even studies about misinformation, despite the fact that its method is in no way scientific."[3]

The site has been used by researchers at the University of Michigan to create a tool called the "Iffy Quotient", which draws data from Media Bias/Fact Check and NewsWhip to track the prevalence of "fake news" and questionable sources on social media.[4][5] The site was also used by a research group at the Massachusetts Institute of Technology in initial training of an AI to fact check and detect the bias on a website.[6][7]

See also[edit]

References[edit]

  1. ^ a b "About". Media Bias/Fact Check. Retrieved 2019-03-30.
  2. ^ a b c Tamar Wilner (January 9, 2018). "We can probably measure media bias. But do we want to?". Columbia Journalism Review.
  3. ^ Funke, Daniel; Mantzarlis, Alexios (December 18, 2018). "Here's what to expect from fact-checking in 2019". Poynter.
  4. ^ Dian Schaffhauser. "U-M Tracker Measures Reliability of News on Facebook, Twitter -- Campus Technology". Campus Technology. Retrieved 2018-12-03.
  5. ^ Paul Resnick; Aviv Ovadya; Garlin Gilchrist. "Iffy Quotient: A Platform Health Metric for Misinformation" (PDF). School of Information - Center for Social Media Responsibility. University of Michigan. p. 5.
  6. ^ Verger, Rob (2018-10-04). "This AI can help spot biased websites and false news". Popular Science. Retrieved 2019-01-01.
  7. ^ Ramy Baly; Georgi Karadzhov; Dimitar Alexandrov; James Glass; Preslav Nakov (2018). "Predicting Factuality of Reporting and Bias of News Media Sources". Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. Brussels, Belgium: Association for Computational Linguistics. pp. 3528–3539.

External links[edit]