In the context of rapid urbanization, the traditional spatial fabric and cultural connotations of historic districts are increasingly threatened, leading to growing problems such as architectural homogenization and weakened public identity. As an important dimension linking spatial form and public cognition, urban memory has gradually become a key entry point for the study of historic district conservation and renewal. At the same time, the large volume of user-generated content accumulated on social media provides a new data foundation and research pathway for architectural and urban memory studies. Taking the Sajinqiao area in Xi’an as the study area, this study uses Weibo texts containing the keyword “Sajinqiao” from 2018 to 2025 as the basic dataset. A Chinese-RoBERTa pretrained language model was employed to identify and screen high-focus Weibo samples, and a classification framework of five types of memory elements was constructed, including roads, areas, nodes, business units, and food entities. On this basis, memory elements were extracted, standardized, and quantified in terms of memory intensity to analyze their evolutionary characteristics. The results show that, first, urban memory in the Sajinqiao area exhibited marked stage-based fluctuations during the study period. Second, business- and consumption-related elements remained dominant in the type structure over the long term. Third, core urban memory was primarily supported by local food entities and related business units, indicating that public memory gradually shifted from experience-oriented memory to destination-oriented memory. This study provides an operational framework for the identification, quantification, and dynamic assessment of urban memory in historic districts, and offers empirical support for memory-oriented conservation and renewal strategies in the Sajinqiao area and similar historic districts.
Xu et al. (Mon,) studied this question.