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The determinants of online customer ratings: a combined domain ontology and topic text analytics approach

Author

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  • Runyu Chen

    (Renmin University of China)

  • Wei Xu

    (Renmin University of China
    Renmin University of China)

Abstract

Merchants, as well as customers, have noticed the importance of online product reviews and numeric ratings in electronic commerce websites. It is valuable if merchants can discover some potential customer value from the sheer volume of data. This paper contributes a semantic text analytics approach that can dig out the customers’ most basic concerns about their online purchase choices. More specifically, based on the hypothesis that the product reviews and overall ratings estimated by same person in a tiny time interval have a great relevance, we dexterously utilize this relevance to realize the embedded customer value. In the proposed method, take the single lens reflex camera for example, an innovative aspect extraction method that comprehensively considers the product ontology and results of the topic modeling method latent Dirichlet allocation is applied. As a result, 8 specific aspects are identified from the experimental results. For each aspect, a self-contained review feature corpus is created as an extension of some seed terms. After aspect-based sentence segmentation and context-sensitive sentiments preprocessing, aspect-oriented sentiment analysis is applied. Multiple regression analysis is then used as a statistical measure to discover determinant aspects of overall ratings. The results reveal that cost performance, image quality and product integrity are the three most influential aspects. The practical implication of our research is that merchants can efficiently modify their products, to satisfy more customers and also boost sales performance.

Suggested Citation

  • Runyu Chen & Wei Xu, 2017. "The determinants of online customer ratings: a combined domain ontology and topic text analytics approach," Electronic Commerce Research, Springer, vol. 17(1), pages 31-50, March.
    • Handle: RePEc:spr:elcore:v:17:y:2017:i:1:d:10.1007_s10660-016-9243-6
    DOI: 10.1007/s10660-016-9243-6
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    References listed on IDEAS

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    Cited by:

    1. Jianping Li & Yinhong Yao & Yuanjie Xu & Jingyu Li & Lu Wei & Xiaoqian Zhu, 2019. "Consumer’s risk perception on the Belt and Road countries: evidence from the cross-border e-commerce," Electronic Commerce Research, Springer, vol. 19(4), pages 823-840, December.
    2. Henrik Sällberg & Shujun Wang & Emil Numminen, 2023. "The combinatory role of online ratings and reviews in mobile app downloads: an empirical investigation of gaming and productivity apps from their initial app store launch," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(3), pages 426-442, September.
    3. Satish Kumar & Weng Marc Lim & Nitesh Pandey & J. Christopher Westland, 2021. "20 years of Electronic Commerce Research," Electronic Commerce Research, Springer, vol. 21(1), pages 1-40, March.

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