Differentiated brand building of traditional mountain scenic spots in Jiangxi Province: Insights from tourists’ perception images and sentiment characteristics

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Abstract

Understanding the perceptions and sentiment responses of tourists to traditional mountain scenic spots is crucial. This understanding is a cornerstone for improving brand image, optimizing space quality, and fostering sentiment connections between tourists and natural landscapes. Our study aims to address the homogenization issue in mountain scenic spots’ brand building. Using online comments and travel blogs as primary data, a mixed-methods approach integrating grounded theory, correspondence analysis, TF-IDF, sentiment analysis, and IPA analysis was employed. The result revealed several significant findings: (1) The tourist perception image represents a multidimensional dynamic system that includes resources, service, sightseeing, and time-space images. Different mountain scenic spots have contrasting characteristics regarding tourism perception images, with the sightseeing image proving a pivotal role in shaping these differences. (2) Among all mountain scenic spots, positive sentiment generally outweighs negative or neutral sentiments, while there are differences in sentiment preferences among perception images. (3) Interactions between tourists’ perception images and their sentiment are fundamental to the establishment of the brand of a scenic site. This research constructs a theoretical model for the generation path of tourism brand image, deepens the understanding of cognitive-affective interactions, improves the perception image system, and provides methodological support for big data-based tourism research. Hence, this study offers insights for the differentiated brand building and sustainable development of traditional mountain scenic spots.

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Hu, Y., Yang, L., & Xu, D. (2025). Differentiated brand building of traditional mountain scenic spots in Jiangxi Province: Insights from tourists’ perception images and sentiment characteristics. PLOS ONE, 20(9 September). https://doi.org/10.1371/journal.pone.0332121

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