Publication: TripAdvisor Restaurant Customer Reviews Analysis in Bangkok, Thailand
| dc.contributor.author | Pleerux N. | |
| dc.contributor.author | Boonpook W. | |
| dc.contributor.author | Chaiyo A. | |
| dc.contributor.author | Nardkulpat A. | |
| dc.contributor.other | Srinakharinwirot University | |
| dc.date.accessioned | 2023-11-15T02:08:54Z | |
| dc.date.available | 2023-11-15T02:08:54Z | |
| dc.date.issued | 2023 | |
| dc.date.issuedBE | 2566 | |
| dc.description.abstract | There are currently a plethora of customer reviews online through websites such as TripAdvisor that can be utilized to satisfy customer needs. This study examined TripAdvisor restaurant reviews in Bangkok during 2007-2021 using the VADER model. Customer reviews were classified into three categories: positive, neutral, and negative. A total of 5,728 restaurants and 105,205 reviews were found from TripAdvisor during the study period. In 2019, it obtained the most reviews with 17,969 while 2016 recorded the most negative reviews. Meanwhile, the COVID19 pandemic has caused a significant decline in the number of reviews. The findings showed that both quantitative and qualitative dimensions of consumer feedbacks on restaurants could be used to improve the restaurant business and adapt to changes in customer preferences. © 2023 IEEE. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.citation | 2023 International Conference on Cyber Management and Engineering, CyMaEn 2023. Vol , No. (2023), p.536-539 | |
| dc.identifier.doi | 10.1109/CyMaEn57228.2023.10050971 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14740/11262 | |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | |
| dc.rights.holder | Scopus | |
| dc.subject.other | Customer satisfaction | |
| dc.subject.other | Natural language processing | |
| dc.subject.other | Sentiment analysis | |
| dc.subject.other | TripAdvisor | |
| dc.subject.other | VADER | |
| dc.title | TripAdvisor Restaurant Customer Reviews Analysis in Bangkok, Thailand | |
| dc.type | Conference Paper | |
| dspace.entity.type | Publication | |
| swu.datasource.scopus | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149996034&doi=10.1109%2fCyMaEn57228.2023.10050971&partnerID=40&md5=5ff32426d1d94d280b3521d83b62c16d |