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On Selecting Recommenders for Trust Evaluation in Online Social Networks

Published:26 November 2015Publication History
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Abstract

Trust is a central component of social interactions among humans. Many applications motivate the consideration of trust evaluation in online social networks (OSNs). Some work has been proposed based on a trusted graph. However, it is still an open challenge to construct a trusted graph, especially in terms of selecting proper recommenders, which can be used to predict the trustworthiness of an unknown target efficiently and effectively. Based on the intuition that people who are close to and influential to us can make more proper and acceptable recommendations, we present the idea of recommendation-aware trust evaluation (RATE). We further model the recommender selection problem as an optimization problem, with the objectives of higher accuracy, lower risk (uncertainty), and lower cost. Four metrics: trustworthiness, expertise, uncertainty, and cost, are identified to measure and adjust the quality of recommenders. We focus on a 1-hop recommender selection, for which we propose the FluidTrust model to better illustrate the trust--decision making process of a user. We also discuss the extension of multihop scenarios and multitarget scenarios. Experimental results, with the real social network datasets of Epinions and Advogato, validate the effectiveness of RATE: it can predict trust with higher accuracy (it gains about 20% higher accuracy in Epinions), lower risk, and less cost (about a 30% improvement).

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    • Published in

      cover image ACM Transactions on Internet Technology
      ACM Transactions on Internet Technology  Volume 15, Issue 4
      Special Issue on Trust in Social Networks and Systems
      December 2015
      88 pages
      ISSN:1533-5399
      EISSN:1557-6051
      DOI:10.1145/2851090
      • Editor:
      • Munindar P. Singh
      Issue’s Table of Contents

      Copyright © 2015 ACM

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 26 November 2015
      • Revised: 1 July 2015
      • Accepted: 1 July 2015
      • Received: 1 July 2014
      Published in toit Volume 15, Issue 4

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