Network Structure and Influencing Factors of Tourist Flow in the Yangtze River Economic Belt: A Study Based on Travelogues

With the high-quality development of the tourism industry and increasing cross-regional cooperation, understanding the evolution and driving mechanisms of tourism flow networks in the Yangtze River Economic Belt (YREB) has become critical. This study constructs a multi-scale tourism flow network across 126 prefecture-level cities using 300,000 travelogues from Ctrip (2015–2019). By integrating social network analysis (SNA) and quadratic assignment procedure (QAP) regression, we decode structural characteristics, node centrality dynamics, and key drivers of network evolution. Key findings include: (1) The network exhibits a multi-nucleated polarization structure centered on Shanghai, Wuhan, and Chongqing, with low overall density and weak connectivity among peripheral cities; (2) Node centrality is highly polarized, emphasizing the agglomeration and radiation capacities of core cities; (3) Primary drivers include the density of 5A/4A scenic spots, tourism infrastructure, per capita GDP, and transportation accessibility. Theoretically, this study advances travel geography by introducing a dynamic, data-driven framework that challenges traditional push-pull theory through digital mediation. By integrating user-generated content (UGC) and multimodal analysis, we pioneer the application of big data to network resilience research, offering insights into algorithmic platforms’ role in reinforcing spatial hierarchies. Our holistic model bridges gaps in multi-scale synergy and multi-factor flow analysis (e.g., tourism, economy, and information flows), providing a foundation for addressing spatial inequalities and informing policies for balanced, sustainable governance.