Internet-famous tourism cities have emerged as a new tourism phenomenon in the digital media era, reflecting changing tourist demands. This study takes three representative internet-famous tourism cities in China, namely Nanjing, Harbin, and Zibo, as cases. Based on large-scale tourist review data, it adopts an attention-enhanced CNN–BiLSTM architecture to develop a multi-level framework for analyzing urban tourism attractiveness. The findings reveal a common Attraction–Experience Mechanism (AEM) underlying urban tourism attractiveness. Rather than being a direct outcome of objective resources, tourism attractiveness emerges relationally as attraction elements are transformed through tourists’ experiences. Differences in how these elements are configured give rise to multiple pathways of attractiveness formation. These findings go beyond the limits of traditional resource determinism, reveal the core logic of contemporary urban tourism attractiveness, and offer insights for enhancing urban competitiveness and promoting sustainable development.
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Lu et al. (2026) studied this question.
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