Against the backdrop of expanding digital dissemination and experiential transformation in cultural heritage, visitors’ visual attention and symbolic choices increasingly shape heritage cognition and value transmission. Taking the Yellow Crane Tower as a case study, this research constructs a cultural symbol recognition dataset based on visitor-shared social media images and develops an enhanced ResNet-50 model for multi-label analysis. By integrating attention mechanisms and regularisation strategies, the model improves its capacity to capture complex cultural imagery, achieving a macro F1 score of 72.70% and a micro F1 score of 81.05% on the test set, indicating strong generalisation performance. The results reveal a significant imbalance in visual preferences: landmark symbols centred on the main architectural structure dominate at 32.95%, whereas culturally informative elements such as signage, cultural products, and interpretive facilities each account for less than 5%. Tag co-occurrence analysis further identifies three image production patterns: commemorative presentation, contextual documentation, and detail-oriented cultural photography reflecting different levels of heritage perception. Rather than directly proposing prescriptive strategies, the findings provide an empirical basis for informing future interventions aimed at shifting from landmark-focused viewing to deeper cultural perception. In this way, the study contributes to heritage display optimisation and research on visitor visual behaviour.
Li et al. (Tue,) studied this question.