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Ranking based on user comments with multiple criteria: the case of Greek restaurants in Athens

Author

Listed:
  • Dimitrios Novas
  • Dimitrios Papakyriakopoulos
  • Elizabeth Powlesland-Kartaloglou
  • Anastasia Griva

Abstract

User generated content (UGC) is a valuable resource for the multi-criteria decision-making process. Platforms, such as TripAdvisor, enable the registration of comments and post rankings. However, existing ranking mechanisms are not transparent, making it impossible to evaluate their integrity and accuracy. Additionally, it has been shown that these rankings are, in some cases, inaccurate and misleading. This prompted the need for developing a ranking mechanism based on UGC to capture experiences and feelings, rather than quantitative data (bubbles/stars). The proposed ranking mechanism employs LDA to generate topics, which are transformed with fuzzy logic to variables, used to produce ranking results. We empirically studied the proposed ranking mechanism using TripAdvisor's user comments on a sample of restaurants located in Athens, Greece and compared the results to a simple quantitative ranking scheme. In some cases, the ranking differed. Further investigation is needed to address the limitations encountered in this research.

Suggested Citation

  • Dimitrios Novas & Dimitrios Papakyriakopoulos & Elizabeth Powlesland-Kartaloglou & Anastasia Griva, 2023. "Ranking based on user comments with multiple criteria: the case of Greek restaurants in Athens," International Journal of Multicriteria Decision Making, Inderscience Enterprises Ltd, vol. 9(3), pages 204-230.
    • Handle: RePEc:ids:ijmcdm:v:9:y:2023:i:3:p:204-230
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