Abstract

This study focused on the growing challenges that Tokyo Airbnb hosts and policymakers face in the holiday homes and home stays market. The study aimed to empower hosts with insights to optimize offerings and assist policymakers in informed decision-making for enhancing neighborhood experiences, with a focus on data-driven business strategies grounded in sentiment analysis. The project employed a robust methodology that leverages sentiment analysis techniques to gain insights from guest comments of Tokyo Airbnb listings spanning from September 2011 to June 2023. The CART algorithm and the Affin sentiment lexicon were used for data cleaning, consolidation, and sentiment analysis. The project aimed to bridge the gap between market popularity and data-driven strategies, ultimately benefiting Tokyo's tourism industry.

Library of Congress Subject Headings

Airbnb (Firm); Vacation rentals--Japan--Tokyo--Management; Sentiment analysis; Tourism--Japan--Tokyo

Publication Date

Spring 2024

Document Type

Thesis

Student Type

Graduate

Degree Name

Professional Studies (MS)

Department, Program, or Center

Graduate Programs & Research

Advisor

Sanjay Modak

Advisor/Committee Member

Ioannis Karamitsos

Campus

RIT Dubai

Plan Codes

PROFST-MS

Download

Share

COinS