Key points are not available for this paper at this time.
This study aims to propose a text mining framework suitable for destination image (DI) research based on UGC (User Generated Content), which combines the LDA (Latent Dirichlet Allocation) model and sentiment analysis method based on custom rules and lexicon to identify and analyze the DI in the emerging ski market. The ski resorts in the host city of the 2022 Winter Olympic Games are selected as a case study. The findings reveal that (1) 9 image attributes, out of which two image attributes have not been identified before in winter destination studies, namely beginner suitability and ticketing service. (2) In the past seven snow seasons, the negative sentiment of tourists has shown a continuous downward trend. The positive sentiment has exhibited a slow upward trend. (3) For tourists from destination countries affected by the Winter Olympic Games, the destination image will be improved when the destination meets their expectations. When the destination cannot meet their expectations, the tourists still believe that the holding of the Winter Olympic will enhance the destination’s situation. The theoretical and managerial implications of these findings are discussed.
Peng et al. (Wed,) studied this question.