“Fake News” Is Not Simply False Information: A Concept Explication and Taxonomy of Online Content
By Maria D. Molina, Shyam Sundar, Thai Le, Dongwon Lee. American Behavioral Scientist, 2019
408 citations recorded by the source corpus.
As the scourge of “fake news” continues to plague our information environment, attention has turned toward devising automated solutions for detecting problematic online content. But, in order to build reliable algorithms for flagging “fake news,” we will need to go beyond broad definitions of the concept and identify distinguishing features that are specific enough for machine learning. With this objective in mind, we conducted an explication of “fake news” that, as a concept, has ballooned to include more than simply false information, with partisans weaponizing it to cast aspersions on the veracity of claims made by those who are politically opposed to them. We identify seven different types of online content under the label of “fake news” (false news, polarized content, satire, misreporting, commentary, persuasive information, and citizen journalism) and contrast them with “real news” by introducing a taxonomy of operational indicators in four domains—message, source, structure, and network—that together can help disambiguate the nature of online news content.
Subfields: Artificial Intelligence, Communication, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/77977b9fdf012c3262755f058df43a3634eed472
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Citations in the corpus
- Fake news, disinformation and misinformation in social media: a review (2023, background): “Moreover, we can find many terms and concepts in the literature that refer to fake news (Van der Linden et al. 2020; Molina et al. 2021) (Abu Arqoub et al. 2022; Allen et al. 2020; Allcott and Gentzkow 2017; Shu et al. 2017; Sharma et al. 2019; Zhou and Zafarani 2020; Zhang and Ghorbani 2020;…”
- User Perceptions and Trust of Explainable Machine Learning Fake News Detectors (2022, background): “However, fake news is distinguished from other types of misinformation 1 in that it is disguised as legitimate news reports to exploit journalistic styles and formats (Molina, Sundar, Le, & Lee, 2021).”
- Teens’ Motivations to Spread Fake News on WhatsApp (2020, background): “…under the headline “Rosalía: This is what ‘Con Altura’ sounds like, the new single by the Catalonian . . . .” The following three cases correspond to three types of misinformation, taking into account different taxonomies (Derakhshan & Wardle, 2017; Molina et al., 2019; Tandoc et al., 2018).”