Measuring Hotel Review Sentiment: An Aspect-Based Sentiment Analysis Approach

• Published in: Integrated Uncertainty in Knowledge Modelling and Decision Making Vol. 11471; pp. 393 - 405
• Main Authors: Tran, Thang, Ba, Hung, Huynh, Van-Nam
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2019; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Annotated hospitality dataset; Aspect-based sentiment analysis; Hotel reviews; Machine learning
• ISBN: 3030148149; 9783030148140
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-030-14815-7_33

Reviews of travelers regarding different characteristics of a hotel are one of the worthiest sources for the managers to enhance their services, facilities, and marketing campaigns. In finding a way to improve the practical experience of both buy-side and sell-side in the hospitality market, we apply sentiment analysis for hospitality data from a user-generated content site named TripAdvisor. Typically, from big data including both quantitative data and qualitative data of customer’s reviews, our contributions are first proposing a framework to utilize big data analysis to identify which aspects/features along with their polarities that customers are focusing, and then inferring and grouping them into 11 topics toward different 405 hotels in Ho Chi Minh City. This study adds more contributions to finding the emerging opinions of customers towards the different topics of hotel reviews by providing an annotated dataset in hotel reviews which ultimately benefits for further research in this field.