Constructing and Quantifying the Urban Gastronomic Destination Image: A Multimodal User-Generated Content Analysis across 12 Chinese Cities

As gastronomic tourism becomes a core growth driver of the global tourism market, leveraging user‑generated content (UGC) to decode urban gastronomic destination image is gaining prominence. Analyzing multimodal UGC (text and images) from Dianping across 12 representative Chinese cities, we propose a parallel, dual‑path framework. Path 1 conducts visual foodscape analysis using network community detection to identify city‑specific gastronomic patterns, indicating a shift from food consumption to cultural experience consumption. Path 2 introduces the Urban Gastronomic Distance Index (UGDI), which integrates entity frequency and rank to quantify intercity differences. Parameter‑sensitivity checks and multidimensional scaling support the stability and validity of UGDI. Results reveal high overall dissimilarity with localized clustering: culturally rooted clusters emerge in the Chengdu–Chongqing and Guangzhou–Foshan pairs, whereas pairs such as Yangzhou–Macao and Chengdu–Foshan exhibit pronounced differences. Notably, the proximity of Tianshui to Sichuan–Chongqing suggests a potential Southwest–Northwest gastronomic transition zone, characterized by shared core symbols with localized adaptations. This study offers a scalable, quantitative tool for cross‑city comparison of gastronomic destination image and provides managerial guidance for regional co‑branding and differentiated positioning.