Shanghai Disney Image Analysis and Improvement Suggestions Based on ROST Text Analysis
- DOI
- 10.2991/978-94-6463-368-9_96How to use a DOI?
- Keywords
- text analysis; sentiment analysis; tourism destination image; Shanghai Disney
- Abstract
Shanghai Disney Park is the Disney Group’s first theme park in mainland China, and its unique charm and strong brand influence have made it a globally popular tourist destination. Since its opening, Shanghai Disney has been super-popular, and some negative comments have arisen. This paper mainly analyses the overall image of Shanghai Disney on social networks. Consumer evaluations on social networks can influence the choices of other consumers, and some negative evaluations may “dissuade” consumers from visiting the park. The focus of this paper is on negative online text reviews, analyzing the causes of negative reviews and proposing targeted solutions to maintain the image of Shanghai Disney as a tourist destination. By crawling the reviews of Shanghai Disney from Dianping, based on the ROST network text analysis method, this paper analyzes the word frequency and semantic sentiment of the positive and negative reviews of Disney tourists, and put forward corresponding improvement suggestions based on the results of the analysis, which can help to promote the satisfaction of tourists, and can also provide experience and references for other theme parks.
- 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 - Meining Gu PY - 2024 DA - 2024/02/14 TI - Shanghai Disney Image Analysis and Improvement Suggestions Based on ROST Text Analysis BT - Proceedings of the 2023 5th International Conference on Economic Management and Cultural Industry (ICEMCI 2023) PB - Atlantis Press SP - 811 EP - 818 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-368-9_96 DO - 10.2991/978-94-6463-368-9_96 ID - Gu2024 ER -