Determination of Guest Satisfaction by Text Mining: Case of Turkey Hotels

Introduction

Since online travel agencies and online reservation media have emerged, many Guests share their experiences about hotels and journeys in these media. Therefore, these media may regard as effective marketing instruments that provide superior benefits (Su, Reynolds and Sun, 2015). Hotel managers were using traditional methods to determine guests’ satisfactions and their behavioral intention. There was survey in the hotel rooms and guests were filling satisfaction surveys after their accommodation in the hotels. However, guests were not willing to give feedback (Ekiz and Au, 2011).

The guests can easily express not only their satisfactions but also their dissatisfactions and they can also use these social media when they decide and select (García-Pablos, Cuadros and Linaza, 2016). In addition, guests certainly use these online platforms when they decide their vacations (Schuckert, Liu and Law, 2015). Analysis of online comments is important for understanding online sales and guest satisfaction.

Since internet media has become an important information source on vacation decisions of guests, the need of research has increased in this field (Spark and Browning, 2011). It is important to analyze guests’ own Comment to understand the guests better and to provide better services.

On the other hand, this chapter uses text mining analysis to analyze text and obtain important results, as it is difficult to analyze large amounts of data on online platforms (Turban, Sharda and Delen, 2010). This study will provide better results compared to previous studies, as it analyzes more data than traditional methods and relies on recommendations from guests (Jannach, Zanker and Fuchs, 2014; Lu and Stepchenkova, 2015; Wang, Chan and Pan, 2015; Gursoy, 2019). There are also specific studies that analyze online comments, determine guests’ attitudes, behavioral intentions and lifestyles, and provide viable marketing strategies (Ghosh, 2018; Moro, Rita and Oliveiar, 2018). Hence this chapter is important to determine guest profile, properties and satisfaction statues of 5-star hotels in Turkey. Besides this study differs from prior studies because it uses a developed emotional analogy method to understand the hotel experiences of hotel guests.

This study aims to determine satisfaction conditions of guests by considering whether guests are satisfied or not by analyzing comments of user about 5-star hotels in Turkey. The text mining method has been selected as the methodology of this study by supposing that significant results can be obtained by huge amount of data from online comments hotel guests. This study consists of four parts. In the first section, the literature on satisfaction and big data analysis in the tourism sector is examined. The second section describes how part of the text mining method works. In the third section, the results obtained for guest satisfaction are presented. In the fourth and final section, results, discussions and suggestions are given.