2024/08/08 by Dasgupta, Subhasis, Roy, Soumya, Jaydip Sen +1
Business, Management and Accounting · #Computation and Language (cs.CL) #Customer Service Quality and Loyalty #FOS: Computer and information sciences #Machine Learning (cs.LG) #Supply Chain Resilience and Risk Management
paper · pdf · doi:10.48550/arxiv.2408.04369
openalex publication_date 2024/08/08 · openalex created_date 2024/11/01 · openalex updated_date 2026/07/28
In the internet era, almost every business entity is trying to have its digital footprint in digital media and other social media platforms. For these entities, word of mouse is also very important. Particularly, this is quite crucial for the hospitality sector dealing with hotels, restaurants etc. Consumers do read other consumers reviews before making final decisions. This is where it becomes very important to understand which aspects are affecting most in the minds of the consumers while giving their ratings. The current study focuses on the consumer reviews of Indian hotels to extract aspects important for final ratings. The study involves gathering data using web scraping methods, analyzing the texts using Latent Dirichlet Allocation for topic extraction and sentiment analysis for aspect-specific sentiment mapping. Finally, it incorporates Random Forest to understand the importance of the aspects in predicting the final rating of a user.