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Mining the Tenant Experience: Uncovering the Determinants of Residential Satisfaction through Topic Modelling of Online Rental Apartment Reviews

Ghasemi, Azin | 2024

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 57004 (44)
  4. University: Sharif University of Technology
  5. Department: Management and Economics
  6. Advisor(s): Aslani, Shirin
  7. Abstract:
  8. Residential satisfaction plays a pivotal role in shaping liveable cities, profoundly influencing individuals' health and well-being. In contrast, dissatisfaction in living environments often triggers relocation intentions, leading to significant vacancy costs for landlords and property managers. While previous studies predominantly relied on traditional methods like surveys and interviews, our research adopts a novel, bottom-up approach, analysing this phenomenon through the lens of residents themselves. Leveraging a custom-developed Python-based web scraper, we meticulously gathered 195,000 online reviews from apartments.com. This comprehensive dataset spans the most populous cities and core-based statistical areas across the United States, representing an unprecedented scale in residential satisfaction research. We utilized Latent Dirichlet Allocation (LDA) to unearth underlying topics within these reviews and employed regression analysis to pinpoint key determinants of residential satisfaction. Our study brings to light the critical human element in residential contentment. It delves into aspects such as community engagement, and the significance of pet and kid-friendliness, underscoring the multifaceted nature of what residents value in their living spaces. Interestingly, we found that approximately 40% of the topics revolve around service dimensions, with package handling services emerging as a newly identified factor in the discourse on residential satisfaction. The insights garnered from our research are invaluable for a range of stakeholders in the real estate sector, particularly property management firms, policymakers, and urban planners. By offering a deeper understanding of the elements that bolster residential satisfaction, this study provides a unique perspective that could shape future strategies and policies, ultimately enhancing the quality of urban living
  9. Keywords:
  10. Topic Modeling ; Latent Dirrichlet Allocation (LDA) ; Residential Satisfaction ; Online Reviews ; Regression Analysis

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