Survival strategies for family-run homestays: Analyzing user reviews through text mining

Krishnanjaykrishnan, Jay, Bhattacharjee, Biplab, Pratap, Maheshwar, Yadav, Janardan Krishna and Maiti, Moinak (2024) Survival strategies for family-run homestays: Analyzing user reviews through text mining. Data Science and Management. ISSN 2666-7649

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Online booking of homestays through e-travel portals is based on the virtual brand and perception, which are largely affected by user-generated electronic word-of-mouth (eWOM). With the objective of mining actionable insights from eWOM, this study conducted opinion mining for homestays located in four thematic areas of Kerala. Accordingly, various techniques have been deployed, such as sentiment and emotional analyses, topic modeling, and clustering methods. Key themes revealed from topic modeling were breakfast, facilities provided, ambience, bathroom, cleanliness, hospitality exhibited, and satisfaction with the host. A lasso logistic regression-based predictive binary text classification model (with 97.6% accuracy) for homestay recommendations was developed. Our findings and predictive model have implications for managers and homestay owners in devising appropriate marketing strategies and improving their overall guest experience.

Item Type: Article
Keywords: Text mining | Tourism | Homestays | Topic modeling | Predictive modeling
Subjects: Social Sciences and humanities > Business, Management and Accounting > Business and International Management
Physical, Life and Health Sciences > Computer Science
JGU School/Centre: Jindal Global Business School
Depositing User: Subhajit Bhattacharjee
Date Deposited: 16 Mar 2024 14:53
Last Modified: 16 Mar 2024 14:53
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