Research on Tourist Satisfaction and Improvement Measures of Wuzhizhou Island Based on Data Mining
- DOI
- 10.2991/978-94-6463-538-6_13How to use a DOI?
- Keywords
- Wuzhizhou Island; data mining; sentiment analysis; LDA topic analysis
- Abstract
As the main service subjects in the tourism industry, the deviation between tourist expectations and the experiential value will directly affect the development of tourist destinations. By using the LDA topic analysis method, 10 tourist attention topics were extracted from tourist comments on Wuzhizhou Island, and the attention degree of each topic was measured. Then, sentiment analysis tools were used to obtain the emotional tendency of tourists from the attention topics, and then to objectively analyze the views of the attention subjects. Finally, the IPA model was used to study the relationship between the weight of each topic and tourist satisfaction. The research results show that the three topics of scenic beauty, transportation within the scenic area, and aesthetic value performed well in terms of tourist attention and satisfaction, highlighting their importance in the tourism of Wuzhizhou Island. However, satisfaction with shopping consumption, route arrangement, and hotel accommodation is relatively low, and improvement and enhancement of service quality are needed.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Ting Lin AU - Qiumi Chen AU - Ling Wang AU - Mengyao Chen PY - 2024 DA - 2024/10/01 TI - Research on Tourist Satisfaction and Improvement Measures of Wuzhizhou Island Based on Data Mining BT - Proceedings of the 4th International Conference on Economic Development and Business Culture (ICEDBC 2024) PB - Atlantis Press SP - 98 EP - 105 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-538-6_13 DO - 10.2991/978-94-6463-538-6_13 ID - Lin2024 ER -