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Robust evaluation of products and reviewers in social rating systems

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Abstract

Social rating systems are widely used to harvest user feedback and to support making decisions by users on the Web. Web users may try to exploit such systems by posting unfair or false evaluations for fame or profit reasons. Detecting the real rating scores of products as well as the trustworthiness of reviewers is an important and a very challenging problem. Existing approaches use majority-based methods along with temporal analysis and clustering techniques to tackle this problem, but they are vulnerable to massive intelligent collaborative attacks. In this paper, we propose a set of novel algorithms for robust computation of product rating scores and reviewer trust ranks. We introduce a supporting framework consisting of three main components responsible for calculating a robust rating score for product, behavior analysis of reviewers and trust computation for reviewers. We propose a novel algorithm for calculating robust rating scores for products, in presence of unfair reviews. We introduce a method to analyze the reviewing behavior of users by building a vector reflecting three important aspects of reviewers’ behavior. Finally, we combine these behavior factors using a fuzzy inference method to arrive at a final trust score for every reviewer. Extensive evaluation results shows accuracy of our calculated rating and trust scores as well as robustness of our methods against collusive attacks.

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Authors and Affiliations

  1. School of Computer Science and Engineering, UNSW, Sydney, NSW, 2052, Australia

    Mohammad Allahbakhsh, Aleksandar Ignjatovic, Hamid Reza Motahari-Nezhad & Boualem Benatallah

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  1. Mohammad Allahbakhsh
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  2. Aleksandar Ignjatovic
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  3. Hamid Reza Motahari-Nezhad
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  4. Boualem Benatallah
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Correspondence to Mohammad Allahbakhsh.

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Allahbakhsh, M., Ignjatovic, A., Motahari-Nezhad, H.R. et al. Robust evaluation of products and reviewers in social rating systems. World Wide Web 18, 73–109 (2015). https://doi.org/10.1007/s11280-013-0242-4

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