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E-WOM and Customer Satisfaction in Robotic vs Traditional Hotels: A Topic Modeling Analysis

Ahmadi, Ali | 2025

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 57947 (44)
  4. University: Sharif University of Technology
  5. Department: Management and Economics
  6. Advisor(s): Aslani, Shirin
  7. Abstract:
  8. This research examines the attributes, themes, and topics discussed in electronic word-of-mouth (e-WOM) generated in TripAdvisor for robotic hotels in comparison to traditional ones. The first objective is to explore the themes and topics within TripAdvisor negative e-WOMs for both types of hotels and analyze how these topics differ between the two types of hotels, using the Latent Dirichlet Allocation (LDA) method. The research shows that which topics are mostly discussed in TripAdvisor negative e-WOMs for both types of hotels. Additionally, the research explores whether different themes, topics, and attributes have varying effects on user ratings in traditional hotels versus robotic ones, employing regression analysis. Findings highlight the key topics in negative e-WOMs, as well as across all types of e-WOM (positive, neutral, and negative), and provide insights into how these topics influence consumer ratings on TripAdvisor for both robotic and traditional hotels
  9. Keywords:
  10. Online Reviews ; Robotic Hotels ; Machine Learning ; Electronic Word to Mouth ; Negative Electronic Word-of-Mouth ; Latent Dirrichlet Allocation (LDA)