Know your hotels well! An online review analysis using text analytics.

Lee, Angela Siew Hoong * and Zaharin Yusoff, * and Zuraini Zainol, and Pillai, V. (2018) Know your hotels well! An online review analysis using text analytics. International Journal of Engineering & Technology, 7 (4.31). pp. 341-437. ISSN 2227-524X

Lee Angela Know_your_Hotels_Well.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial.

Download (525kB) | Preview
Official URL:


Online travel forums have become an extremely popular platform for sharing travel information, with a large number of reviews being posted daily. Travel websites such as TripAdvisor and have turned into very important resources for hotel operators and travellers alike, for promoting hotel rooms, choosing hotels as well as for soliciting and sharing feedback. Criticisms, compliments, dissensions, etc., are now accessible anytime and anywhere on the web, and can be readily amassed, while opinion mining techniques have developed rapidly. Together they provide the opportunity and capability to analyse and deduce factors that influence travellers in their choice of hotels. In this paper, we apply opinion mining on data collected from Tripadvisor websites. In total, 11,130 reviews on 4 hotels within the four-star and five-star categories in Kuala Lumpur are crawled, collected, and mined to identify the top-k most predominant information based on the most frequent and most related terms used in describing each of the chosen hotels. The results of this study would allow travellers to see the opinions of other travellers on these hotels, and hotel operators would be able to receive feedback to improve their services and in turn promote their hotels. This study is also carried out in view of future improvements in the techniques used and the analysis performed.

Item Type: Article
Uncontrolled Keywords: opinion mining; text mining; hotel reviews; customer satisfaction; SAS TexMiner
Subjects: Q Science > QA Mathematics > QA76 Computer software
T Technology > TX Home economics
Divisions: Others > Non Sunway Academics
Sunway University > School of Engineering and Technology [formerly School of Science and Technology until 2020] > Dept. Computing and Information Systems
Depositing User: Dr Janaki Sinnasamy
Related URLs:
Date Deposited: 24 May 2019 05:07
Last Modified: 07 Oct 2020 04:51

Actions (login required)

View Item View Item