Analyzing the cultural landscape of Chinese art districts through online social media: a text mining and theoretical interpretation using user-generated content

Abstract

The study examines three Chinese art districts, namely Beijing 798, Hangzhou Xiangshan Art Commune, and Jingdezhen Taoxichuan, using 28,661 social media posts. By integrating semantic networks, irony-aware sentiment analysis, and LDA (Latent Dirichlet Allocation) modeling. The results show that 40% of respondents were neutral about Hangzhou’s new spaces, 63.8% were supportive of Jingdezhen’s historical revitalization, and 31.2% were against Beijing 798’s over-commercialization. A dynamic equilibrium theory is proposed to balance growth and heritage by advancing Lefebvre’s spatial triad. In terms of methodology, combining cultural theory with digital humanities technologies is likely to provide insights into digital-era participatory placemaking and urban redevelopment.