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Foundations of Trust and Distrust in Networks: Extended Structural Balance Theory

Published:08 July 2014Publication History
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Abstract

Modeling trust in very large social networks is a hard problem due to the highly noisy nature of these networks that span trust relationships from many different contexts, based on judgments of reliability, dependability, and competence. Furthermore, relationships in these networks vary in their level of strength. In this article, we introduce a novel extension of structural balance theory as a foundational theory of trust and distrust in networks. Our theory preserves the distinctions between trust and distrust as suggested in the literature, but also incorporates the notion of relationship strength that can be expressed as either discrete categorical values, as pairwise comparisons, or as metric distances. Our model is novel, has sound social and psychological basis, and captures the classical balance theory as a special case. We then propose a convergence model, describing how an imbalanced network evolves towards new balance, and formulate the convergence problem of a social network as a Metric Multidimensional Scaling (MDS) optimization problem. Finally, we show how the convergence model can be used to predict edge signs in social networks and justify our theory through extensive experiments on real datasets.

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      • Published in

        cover image ACM Transactions on the Web
        ACM Transactions on the Web  Volume 8, Issue 3
        June 2014
        256 pages
        ISSN:1559-1131
        EISSN:1559-114X
        DOI:10.1145/2639948
        Issue’s Table of Contents

        Copyright © 2014 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 8 July 2014
        • Accepted: 1 March 2014
        • Revised: 1 December 2013
        • Received: 1 June 2013
        Published in tweb Volume 8, Issue 3

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