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Investigating negative reviews and detecting negative influencers in Yelp through a multi-dimensional social network based model

Author

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  • Corradini, Enrico
  • Nocera, Antonino
  • Ursino, Domenico
  • Virgili, Luca

Abstract

In this paper, we propose an investigation of negative reviews and define the profile of negative influencers in Yelp. The methodology adopted to achieve this goal consists of two phases. The first one is theoretical and aims at defining a multi-dimensional social network based model of Yelp, three stereotypes of Yelp users, and a network based model to represent negative reviewers and their relationships. The second phase is experimental and consists in the definition of five hypotheses on negative reviews and reviewers in Yelp and their verification through an extensive data analysis campaign. This was performed on Yelp data represented by means of the models introduced during the first phase. Its most important result is the construction of the profile of negative influencers in Yelp. The main novelties of this paper are: (i) the definition of the two social network based models of Yelp and its users; (ii) the definition of three stereotypes of Yelp users and their characteristics; (iii) the construction of the profile of negative influencers in Yelp.

Suggested Citation

  • Corradini, Enrico & Nocera, Antonino & Ursino, Domenico & Virgili, Luca, 2021. "Investigating negative reviews and detecting negative influencers in Yelp through a multi-dimensional social network based model," International Journal of Information Management, Elsevier, vol. 60(C).
    • Handle: RePEc:eee:ininma:v:60:y:2021:i:c:s0268401221000700
    DOI: 10.1016/j.ijinfomgt.2021.102377
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    Cited by:

    1. Guanghui Wang & Yushan Wang & Kaidi Liu & Shu Sun, 2024. "A classification and recognition algorithm of key figures in public opinion integrating multidimensional similarity and K-shell based on supernetwork," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-19, December.

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