Let’s CoRank: trust of users and tweets on social networks

Springer Science and Business Media LLC
Publication Type:
Journal Article
World Wide Web, 2020, 23, (5), pp. 2877-2901
Issue Date:
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Li2020_Article_LetSCoRankTrustOfUsersAndTweet.pdfPublished version1.38 MB
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© 2020, Springer Science+Business Media, LLC, part of Springer Nature. Twitter, as one of the largest Online Social Network (OSN) platforms, is a popular media for online social communication and information dissemination. The trustworthy evaluation of information and people becomes crucial for maintaining an open and healthy OSN for our society. In this work, we develop a Coupled Dual Networks Trust Ranking (CoRank) method to evaluate the trustworthiness of users and tweets by analysing user/tweet behaviours on Twitter. We propose a model to capture the complex characteristics and relations of both users and tweets and calculate their trust values. Our approach goes beyond the existing solutions that use a single network to link both users and tweets. A set of experiments have been conducted against the real data collected from Twitter. The experimental results show the effectiveness, robustness, and time complexity of the proposed method. We also compare our solution with three baseline methods PageRank, TURank, and Weighted PageRank, to show how our approach outperforms the existing ones.
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