| Author | Itsaree Khumtaveeporn |
| Call Number | AIT RSPR no.SM-23-06 |
| Subject(s) | Tourism--Mathematical models
Tourism--Data processing
|
| Note | A Research Study Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science in Business Analytics & Digital Transformation |
| Publisher | Asian Institute of Technology |
| Abstract | In this study, sentiment analysis is used to identify unique experiences of tourists for destination branding. The author used Latent Dirichlet Allocation for big data analysis to discover unique attributes, and TextBlob-Flair to assess sentiment. TripAdvisor reviews of tourist attractions in Buriram, Thailand serve as a case study. The findings reveal that tourists highly rated Buriram\'s archaeological sites and sports attractions, indicating that the Tourism Authority of Thailand should focus on branding Buriram as a unique destination that blends modernization with rich historical significance. The results demonstrate the effectiveness of sentiment analysis in revealing patterns in large amounts of text that may not be immediately apparent to human readers. Therefore, it is evident that this novel approach can be utilized to discover unique attributes for destination branding |
| Year | 2023 |
| Type | Research Study Project Report (RSPR) |
| School | School of Management |
| Department | Other Field of Studies (No Department) |
| Academic Program/FoS | Master of Science in Business Analytics and Digital Transformation (M/Msc BADT) |
| Chairperson(s) | Kritsadarat Wattanasuwan ;Levermore, Roger (Co-Chairperson) |
| Examination Committee(s) | Ransom, Lakeesha K. ;Endress, Tobias; |
| Scholarship Donor(s) | His Majesty the King of Thailand,; |
| Degree | Research studies project report (M. Sc.) - Asian Institute of Technology, 2023 |
