Analyzing and distinguishing fake and real news to mitigate the problem of disinformation

Alina Vereshchaka (), Seth Cosimini () and Wen Dong ()
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Alina Vereshchaka: University at Buffalo
Seth Cosimini: University of Nevada, Reno
Wen Dong: University at Buffalo

Computational and Mathematical Organization Theory, 2020, vol. 26, issue 3, No 5, 350-364

Abstract: Abstract Identifying fake news has become an important issue. Increasing usage of social media has led to an increase in the number of people who can be influenced, thus the spread of fake news can potentially impact important events. Fake news has become a major societal issue and a technical challenge for social media companies to identify and has led many to extreme measures, such as WhatsApp deleting two million of its users every month to prevent the spread of fake news. The current problem of fake news is rooted in the historical problem of disinformation, which is false information intentionally, and usually clandestinely, disseminated to manipulate public opinion or obfuscate the truth. Our work addresses the problem of identifying fake news by (i) detecting and analyzing fake news features (ii) identifying the textual and sociocultural characteristics fake news features.

Keywords: Fake news; Real news; Fake news identification; Data analysis; Deep learning; Sociocultural textual analysis (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10588-020-09307-8

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