4.6 Article

EXPRS: An extended pagerank method for product feature extraction from online consumer reviews

期刊

INFORMATION & MANAGEMENT
卷 52, 期 7, 页码 850-858

出版社

ELSEVIER
DOI: 10.1016/j.im.2015.02.002

关键词

Online product reviews; Feature extraction; Extended PageRank algorithm; Synonym expansion; Social media analytics

资金

  1. National Natural Science Foundation of China [71128003, 71272057]
  2. National Key Technology Support Program [2013BAH16F00]

向作者/读者索取更多资源

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. (C) 2015 Elsevier B.V. All rights reserved.

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