Research on China’s rural tourism destination image for users with different experience attributes based on text mining method

Le résumé fourni par la source

Rural tourism is an important market segment of tourism. Tourists with differing travel experiences have different perceptions of the rural tourism destination image. For mining the destination image accurately, this study proposed a deep emotion classification framework to mine online comments and extract the differences in perceptions of diverse experience groups. Specifically, first, the BERT emotion classification model was introduced to identify positive and negative comments. Second, the emotional keywords were extracted using PaddleNLP to reveal the perception of tourists with different experiences. Correspondingly, the results showed that the majority of tourists hold a favourable view of rural tourism. Various types of tourists have different concerns and priorities for the rural tourism destination image. Finally, suggestions were put forward from aspects such as reasonable charging and improving traffic conditions to provide support for rural tourism destination image management, optimisation and targeted marketing.

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