Article ID: | iaor201527682 |
Volume: | 52 |
Issue: | 7 |
Start Page Number: | 850 |
End Page Number: | 858 |
Publication Date: | Nov 2015 |
Journal: | Information & Management |
Authors: | Zhang Dongsong, Yan Zhijun, Xing Meiming, Ma Baizhang |
Keywords: | e-commerce, computers: information, management, decision |
Online consumer product reviews are a main source for consumers to obtain product information and reduce product uncertainty before making a purchase decision. However, the great volume of product reviews makes it tedious and ineffective for consumers to peruse individual reviews one by one and search for comments on specific product features of their interest. This study proposes a novel method called EXPRS that integrates an extended PageRank algorithm, synonym expansion, and implicit feature inference to extract product features automatically. The empirical evaluation using consumer reviews on three different products shows that EXPRS is more effective than two baseline methods.