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What are consumers saying online about your products? Mining the text of online reviews to uncover hidden features

Author

Listed:
  • Alzate, Miriam

    (Department of Management, Los Madroños Building, Campus Arrosadia s/n, Public University of Navarre, Spain)

  • Arce-Urriza, Marta

    (Department of Management, Los Madroños Building, Campus Arrosadia s/n, Public University of Navarre, Spain)

  • Cebollada, Javier

    (Department of Management, Los Madroños Building, Campus Arrosadia s/n, Public University of Navarre, Spain)

Abstract

Thanks to the growth of the internet and the increasing use of social networks, companies can now access huge volumes of online texts in order to understand consumers’ preferences and needs. This article illustrates some methods to extrapolate information from such texts. The text-mining analysis covers such issues as word frequency, sentiment analysis, paired words, similarities in textual content and the main topics discussed in online reviews. From a practical point of view, brand managers can use the proposed methods to gain consumer insights into products and brands, to be able to improve and adapt their marketing strategies.

Suggested Citation

  • Alzate, Miriam & Arce-Urriza, Marta & Cebollada, Javier, 2021. "What are consumers saying online about your products? Mining the text of online reviews to uncover hidden features," Journal of Digital & Social Media Marketing, Henry Stewart Publications, vol. 9(2), pages 169-186, September.
    • Handle: RePEc:aza:jdsmm0:y:2021:v:9:i:2:p:169-186
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    More about this item

    Keywords

    eWOM; online reviews; text mining; sentiment analysis; topic modelling;
    All these keywords.

    JEL classification:

    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising

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