Abstract
The emergence of the COVID-19 in 2019 has unquestionably had a profound and transformative effect on the tourism industry. Following the easing of COVID-19 prevention and control measures in China, there has been a significant increase in travel demand. Representing the epitome of excellence in Chinese scenic spots, 5A-class scenic areas are primary destinations for travelers. The assessment of these scenic spots plays a crucial role in shaping their tourism reputation. Currently, there is a regional focus in research on the evaluation of 5A-class scenic spots exhibits regional characteristics, with limited attention given to a nationwide assessment. In this study, we collected over 410,000 online comments were gathered from 256 scenic spots classified as 5A-class. Employing the Latent Dirichlet Allocation (LDA) topic model, this study conducted a thematic exploration and applied Grounded Theory for qualitative analysis of evaluation themes. This study focused on analyzing scenic spot evaluations by examining three dimensions: the scenic spot itself, the surrounding facilities, and the perspective of tourists. Study findings reveal: (1)Tourist evaluations of 5A-class scenic spots by tourists undergo changes from the inception of the journey to its conclusion. (2)Tourist assessments of these scenic spots are not confined solely to the attractions themselves, the quality of peripheral amenities also has a significant impact on their assessments. This study differentiates itself from traditional regional analysis and perceptual image perspective analysis by employing a process-oriented approach from the perspective of the tourist. The utilization of text-mining techniques enables the identification of coexisting universal and regional tourism evaluation indicators. The present study makes a valuable contribution to the existing body of knowledge by providing insights into the intricate nature of the tourist evaluation process and the interrelationships among different factors.
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