Sentiment analysis of hotel reviews in Singapore
Tourism industry is one of the major industries in Singapore, attracting a total number of 17.4 million of international tourists in 2017. This industry is poised to grow further with a recorded total number of 18.5 million of international tourists visited Singapore in 2018, an increase of 6.2% com...
| Main Author: | |
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| Format: | Dissertation (University of Nottingham only) |
| Language: | English |
| Published: |
2020
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| Online Access: | https://eprints.nottingham.ac.uk/59490/ |
| _version_ | 1848799635690225664 |
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| author | Wong, Wai Ming |
| author_facet | Wong, Wai Ming |
| author_sort | Wong, Wai Ming |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Tourism industry is one of the major industries in Singapore, attracting a total number of 17.4 million of international tourists in 2017. This industry is poised to grow further with a recorded total number of 18.5 million of international tourists visited Singapore in 2018, an increase of 6.2% compared to 2017 (www.stb.gov.sg, 2019). As hotel stay will be one of the major factors in tourist experience, we will examine the drivers of sentiments of online hotel reviews, overall sentiments towards hotels in Singapore and the useful insights and recommendations that hoteliers can adopt from existing sentiments of online hotel reviews. About 18943 online reviews were extracted from Tripadvisor.com and 1855 reviews were extracted from Hotels.com and text analytics were carried out using RapidMiner whereas sentiment analysis was carried out using Aylien text analytics. The research outcome indicated that customers sentiments are generally positive and key drivers influencing customer sentiments are service, food, location, room, facility, brand loyalty / image and price. |
| first_indexed | 2025-11-14T20:38:48Z |
| format | Dissertation (University of Nottingham only) |
| id | nottingham-59490 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:38:48Z |
| publishDate | 2020 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-594902020-08-05T08:00:27Z https://eprints.nottingham.ac.uk/59490/ Sentiment analysis of hotel reviews in Singapore Wong, Wai Ming Tourism industry is one of the major industries in Singapore, attracting a total number of 17.4 million of international tourists in 2017. This industry is poised to grow further with a recorded total number of 18.5 million of international tourists visited Singapore in 2018, an increase of 6.2% compared to 2017 (www.stb.gov.sg, 2019). As hotel stay will be one of the major factors in tourist experience, we will examine the drivers of sentiments of online hotel reviews, overall sentiments towards hotels in Singapore and the useful insights and recommendations that hoteliers can adopt from existing sentiments of online hotel reviews. About 18943 online reviews were extracted from Tripadvisor.com and 1855 reviews were extracted from Hotels.com and text analytics were carried out using RapidMiner whereas sentiment analysis was carried out using Aylien text analytics. The research outcome indicated that customers sentiments are generally positive and key drivers influencing customer sentiments are service, food, location, room, facility, brand loyalty / image and price. 2020-07-24 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/59490/1/Wong%20Wai%20Ming-converted.pdf Wong, Wai Ming (2020) Sentiment analysis of hotel reviews in Singapore. [Dissertation (University of Nottingham only)] big data data analytics sentiment analysis online hotel reviews Singapore hotels |
| spellingShingle | big data data analytics sentiment analysis online hotel reviews Singapore hotels Wong, Wai Ming Sentiment analysis of hotel reviews in Singapore |
| title | Sentiment analysis of hotel reviews in Singapore |
| title_full | Sentiment analysis of hotel reviews in Singapore |
| title_fullStr | Sentiment analysis of hotel reviews in Singapore |
| title_full_unstemmed | Sentiment analysis of hotel reviews in Singapore |
| title_short | Sentiment analysis of hotel reviews in Singapore |
| title_sort | sentiment analysis of hotel reviews in singapore |
| topic | big data data analytics sentiment analysis online hotel reviews Singapore hotels |
| url | https://eprints.nottingham.ac.uk/59490/ |