A combined approach based on fuzzy AHP and fuzzy inference system to rank reviewers in online communities

Authors: HOSSEIN ABBASIMEHR, MOHAMMADJAFAR TAROKH

Abstract: Online product review communities allow users to share their ideas and opinions about various products and services. Although online reviews as user-generated content can be considered as an invaluable source of information for both consumers and firms, these reviews tend to be of very different quality. To tackle the problem of low quality reviews, we address reviewer credibility and propose an innovative framework. The framework comprises five critical phases for ranking reviewers in terms of credibility using a fuzzy analytic hierarchy process (AHP) and fuzzy inference system. To determine the weights of the features, a fuzzy AHP method was applied. In addition, according to the proposed framework, to compute a realistic credibility score based on trustworthiness and expertise, a cognitive approach was followed and a fuzzy inference system was designed. To illustrate an application of the proposed method, we conducted an experimental study using real data gathered from Epinions.

Keywords: Social web, online reviews, reviewer credibility, trust network, fuzzy analytic hierarchy process, fuzzy inference systems

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