A Hybrid Framework For Ranking Reviewers Based On Interval Type-2 Fuzzy Ahp And Vikor

Online reviews are crucial resources both for users and business enterprises. However, the quality of online reviews varies greatly. To address the problem of low-quality reviews, we focus on the problem of reviewer credibility and propose a new framework. The proposed framework incorporates three main parts including identification of source credibility factors, preprocessing, and ranking via interval type-2 fuzzy analytical hierarchy process (IT2FAHP) and VIKOR method. A major distinction of the proposed framework is utilising multiple factors obtained from different sources, which leads to considerably improved reviewers ranking. Furthermore, we propose a new method for defuzzification of interval type-2 fuzzy sets that yields more reasonable results when compared with the existing methods. The framework is evaluated using real data crawled from Epinions. The results indicated that the proposed framework effectively ranks the reviewers based on their credibility.