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 . doi:10.1145/3382188 (In Press)

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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:	5 February 2020
Dates:	Date Event 5 February 2020 Accepted
Date of first compliant deposit:	12 February 2020
DOI:	10.1145/3382188
Status:	Peer Reviewed
Publication Status:	In Press
Publisher Statement:	© 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 {Source Publication}, http://dx.doi.org/10.1145/3382188
Access rights to Published version:	Restricted or Subscription Access
Related URLs:	Publisher

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