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Online customer reviews are a sustainable form of word of mouth (WOM) which play an increasingly important role in e-commerce. However, low quality reviews can often cause inconvenience to review readers. The purpose of this paper is to automatically predict the helpfulness of reviews. This paper analyzes the characteristics embedded in product reviews across five different product types and explores their effects on review helpfulness. Furthermore, four data mining methods were examined todoi:10.3390/su10061735 fatcat:4ql3ldautzhubfi37pkhcjtyiu