Using Geodetector to explore the factors affecting evolution of the spatial structure of information flow in the middle reaches of the Yangtze River urban agglomeration

This paper explores the influence of the real-world urban attributes on the information flow among cities. UCINET was used to analyze the evolution of the spatial structure of information flow (SSIF). The Geodetector is applied to identify the spatial stratified correlation between the SSIF and urban attributes. The authors choose indicators such as economy, scale and facilities as background indicators. Furthermore, based on the textual categorization of the Baidu urban demand map, we selected the factors that people search more frequently as the direct factors. We conduct empirical analysis with the middle reaches of the Yangtze River urban agglomeration (MYUA) as a typical case. Our results show that the gap between cities is gradually decreasing in the information flow space. In the initial stage, the dominant factors affecting information flow network are mostly background factors. With the development of infrastructure and the increase in internet users, the density of information network is gradually increasing, and the structure of urban network tends to flatten. Direct factors gradually become the dominant factor affecting the evolution of network. The interactions of multiple factors had a stronger impact on the information network than individual factors.