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Using probabilistic confidence models for trust inference in Web-based social networks

Published:10 June 2010Publication History
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Abstract

In this article, we describe a new approach that gives an explicit probabilistic interpretation for social networks. In particular, we focus on the observation that many existing Web-based trust-inference algorithms conflate the notions of “trust” and “confidence,” and treat the amalgamation of the two concepts to compute the trust value associated with a social relationship. Unfortunately, the result of such an algorithm that merges trust and confidence is not a trust value, but rather a new variable in the inference process. Thus, it is hard to evaluate the outputs of such an algorithm in the context of trust inference.

This article first describes a formal probabilistic network model for social networks that allows us to address that issue. Then we describe SUNNY, a new trust inference algorithm that uses probabilistic sampling to separately estimate trust information and our confidence in the trust estimate and use the two values in order to compute an estimate of trust based on only those information sources with the highest confidence estimates.

We present an experimental evaluation of SUNNY. In our experiments, SUNNY produced more accurate trust estimates than the well-known trust inference algorithm TidalTrust, demonstrating its effectiveness. Finally, we discuss the implications these results will have on systems designed for personalizing content and making recommendations.

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  • Published in

    cover image ACM Transactions on Internet Technology
    ACM Transactions on Internet Technology  Volume 10, Issue 2
    May 2010
    123 pages
    ISSN:1533-5399
    EISSN:1557-6051
    DOI:10.1145/1754393
    Issue’s Table of Contents

    Copyright © 2010 ACM

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 10 June 2010
    • Accepted: 1 November 2009
    • Revised: 1 July 2009
    • Received: 1 November 2008
    Published in toit Volume 10, Issue 2

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