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