Know your hotels well! An online review analysis using text analytics.
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 Booking.com have turned into very important resources for hotel operators and travellers alike, for promoting hot...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Science Publishing Corporation, UAE
2018
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| Online Access: | http://eprints.sunway.edu.my/1046/ http://eprints.sunway.edu.my/1046/1/Lee%20Angela%20Know_your_Hotels_Well.pdf |
| _version_ | 1848801949332275200 |
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| author | Lee, Angela Siew Hoong * Zaharin Yusoff, * Zuraini Zainol, Pillai, V. |
| author_facet | Lee, Angela Siew Hoong * Zaharin Yusoff, * Zuraini Zainol, Pillai, V. |
| author_sort | Lee, Angela Siew Hoong * |
| building | SU Institutional Repository |
| collection | Online Access |
| description | 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 Booking.com 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. |
| first_indexed | 2025-11-14T21:15:35Z |
| format | Article |
| id | sunway-1046 |
| institution | Sunway University |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T21:15:35Z |
| publishDate | 2018 |
| publisher | Science Publishing Corporation, UAE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | sunway-10462020-10-07T04:51:09Z http://eprints.sunway.edu.my/1046/ Know your hotels well! An online review analysis using text analytics. Lee, Angela Siew Hoong * Zaharin Yusoff, * Zuraini Zainol, Pillai, V. QA76 Computer software TX Home economics 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 Booking.com 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. Science Publishing Corporation, UAE 2018-11 Article PeerReviewed text en cc_by_nc_4 http://eprints.sunway.edu.my/1046/1/Lee%20Angela%20Know_your_Hotels_Well.pdf 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 https://www.sciencepubco.com/index.php/IJET |
| spellingShingle | QA76 Computer software TX Home economics Lee, Angela Siew Hoong * Zaharin Yusoff, * Zuraini Zainol, Pillai, V. Know your hotels well! An online review analysis using text analytics. |
| title | Know your hotels well! An online review analysis using text analytics. |
| title_full | Know your hotels well! An online review analysis using text analytics. |
| title_fullStr | Know your hotels well! An online review analysis using text analytics. |
| title_full_unstemmed | Know your hotels well! An online review analysis using text analytics. |
| title_short | Know your hotels well! An online review analysis using text analytics. |
| title_sort | know your hotels well! an online review analysis using text analytics. |
| topic | QA76 Computer software TX Home economics |
| url | http://eprints.sunway.edu.my/1046/ http://eprints.sunway.edu.my/1046/ http://eprints.sunway.edu.my/1046/1/Lee%20Angela%20Know_your_Hotels_Well.pdf |