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http://dx.doi.org/10.3745/JIPS.04.0217

Analyzing Customer Experience in Hotel Services Using Topic Modeling  

Nguyen, Van-Ho (School of Business Information Technology, University of Economics Ho Chi Minh City)
Ho, Thanh (Faculty of Information Systems, University of Economics and Law)
Publication Information
Journal of Information Processing Systems / v.17, no.3, 2021 , pp. 586-598 More about this Journal
Abstract
Nowadays, users' reviews and feedback on e-commerce sites stored in text create a huge source of information for analyzing customers' experience with goods and services provided by a business. In other words, collecting and analyzing this information is necessary to better understand customer needs. In this study, we first collected a corpus with 99,322 customers' comments and opinions in English. From this corpus we chose the best number of topics (K) using Perplexity and Coherence Score measurements as the input parameters for the model. Finally, we conducted an experiment using the latent Dirichlet allocation (LDA) topic model with K coefficients to explore the topic. The model results found hidden topics and keyword sets with high probability that are interesting to users. The application of empirical results from the model will support decision-making to help businesses improve products and services as well as business management and development in the field of hotel services.
Keywords
Customer Experience; Hotel Services; LDA; Text Mining; Topic Modeling;
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