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

Zhijun Yan, Meiming Xing, Dongsong Zhang*, Baizhang Ma

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    118 Citations (Scopus)

    Abstract

    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.

    Original languageEnglish
    Pages (from-to)850-858
    Number of pages9
    JournalInformation and Management
    Volume52
    Issue number7
    DOIs
    Publication statusPublished - 1 Nov 2015

    Keywords

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

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