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Customer satisfaction is an important scale for the product's quality of the companies. Companies are always looking for the ways to understand customer's psychology and demand for the product that they offer and maintain the customer's loyalty (Parra-Lopez et al., 2018). In the digital age, the way to understand customers' psychology is also applied with modern technologies and measurement (Eryilmaz, 2019). There are many algorithms and methods have been proposed. In which, the field of customers' opinion mining and sentiment analysis are attracting companies recently (Annisa et al., 2019). When combining with machine learning and natural language processing technique it can exploit and analyze the big data, it really a powerful tool to understand sentiment and feelings of customers for the products and services that the companies provided (A. R. Alaei et al., 2019; W. Chen et al., 2020; de Souza et al., 2018).
Tourism industry is an extremely technology-sensitive field. In the digital knowledge era like today, the Internet, online commerce systems and social networks are exploding in all fields (A. R. Alaei et al., 2019; Eryilmaz, 2019). Tourism is also not out of this trend. Online booking sites make easier for travelers to plan their travel somewhere, they have the freedom to choose hotels according to their desired standards, and more importantly, online booking sites like tripadvisor, seemingly know what guests need, these technology systems provide a private space for customers to create their content (A. R. Alaei et al., 2019). Experiences of guest about destinations and tourism services are a big supporting to potential guests in booking decisions (Jayathilaka et al., 2020; Zheng et al., 2018). Sentiments extract from guests’ feedback can be used as valuable input for managerial decisions (figure 1), or a reliable source of recommendations for potential guest (Zheng et al., 2018), (Jayathilaka et al., 2020). In commonly, positive feedback indicating guest satisfaction about the service provided and otherwise, negative feedback indicates guest dissatisfaction (Xiang, Schwartz, Gerdes, et al., 2015; Narangajavana Kaosiri et al., 2019).
Figure 1. A review on the TripAdvisor site
Hotel online review data is very large and available (Iorio et al., 2019; Said & Muqrashi, 2020). It would be waste if we do not exploit information from this data source because they contain a lot of meaningful information for understanding customers' psychology and emotions . However, because they are so large and increase over time so that, they cannot be exploited manually (Kirilenko et al., 2018). A new field has emerged in recent years, instead of previous traditional method for customer data mining such as questionnaires and face-to-face interviews. It can take advantage of existing data source to exploit the customer's opinion. That is the opinion mining and sentiment analysis field. For e-commerce field that said, sentiment analysis has helped a lot in assessing customer perceptions of products of sentiment classification (Zapata et al., 2019). For the hotel domain, it can be extended further more as measuring guest satisfaction, guest loyalty and hotel ratings (Parra-Lopez et al., 2018; Imane & Abdelouahab, 2019).