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Many scholars use big data analysis methods to investigate tourist destination image. However, research on the internal relations between the key elements of tourist destination image and its revolution trends is rare, especially with respect to seasonal trends. To bridge this gap in the literature, our research is the first to comprehensively use multiple big data analysis methods to explore tourist destination image based on tourist gaze theory. By analyzing 22,035 tourists’ reviews of Huangshan, we had three main findings: First, ‘convenient’, ‘worthy’, ‘beautiful scenery’, ‘satisfactory’, ‘adequate facilities’, and ‘great experience’ are the six main tourism destination image dimensions of Huangshan; second, the keywords of each dimension display various co-occurrence relations; finally, the tourism destination image dimensions exhibit different seasonal trends over time. Our study not only greatly enhances the existing literature, but also provides important practical implications for destination marketing organizations.

Do tourists’ perceptions of tourism destination change across seasons? A mixed big data analysis