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Real or not? Identifying untrustworthy news websites using third-party partnerships

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Gopal, Ram, Hidaji, Hooman, Kutlu, Sule, Patterson, Raymond A., Rolland, Erik and Zhdanov, Dmitry (2020) Real or not? Identifying untrustworthy news websites using third-party partnerships. ACM Transactions on Management Information Systems, 11 (3). 10. doi:10.1145/3382188 ISSN 2158-656X.

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Official URL: https://doi.org/10.1145/3382188

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Abstract

Untrustworthy content such as fake news and clickbait have become a pervasive problem on the Internet, causing significant socio-political problems around the world. Identifying untrustworthy content is a crucial step in countering them. The current best-practices for identification involve content analysis and arduous fact-checking of the content. To complement content analysis, we propose examining websites? third-parties to identify their trustworthiness. Websites utilize third-parties, also known as their digital supply chains, to create and present content and help the website function. Third-parties are an important indication of a website?s business model. Similar websites exhibit similarities in the third-parties they use. Using this perspective, we use machine learning and heuristic methods to discern similarities and dissimilarities in third-party usage, which we use to predict trustworthiness of websites. We demonstrate the effectiveness and robustness of our approach in predicting trustworthiness of websites from a database of News, Fake News, and Clickbait websites. Our approach can be easily and cost-effectively implemented to reinforce current identification methods.

Item Type: Journal Article
Subjects: H Social Sciences > HE Transportation and Communications
J Political Science > JC Political theory
P Language and Literature > PN Literature (General) > PN0080 Criticism
Q Science > QA Mathematics
Divisions: Faculty of Social Sciences > Warwick Business School
Library of Congress Subject Headings (LCSH): Fake news , Disinformation, Digital media , Heuristic algorithms, Online journalism, Web sites -- Evaluation, Social conflict in mass media
Journal or Publication Title: ACM Transactions on Management Information Systems
Publisher: ACM
ISSN: 2158-656X
Official Date: August 2020
Dates:
DateEvent
August 2020Published
30 July 2020Available
5 February 2020Accepted
Volume: 11
Number: 3
Article Number: 10
DOI: 10.1145/3382188
Status: Peer Reviewed
Publication Status: Published
Reuse Statement (publisher, data, author rights): © Author | ACM 2020. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Transactions on Management Information Systems http://dx.doi.org/10.1145/3382188
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 12 February 2020
Date of first compliant Open Access: 12 February 2020
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