The Method and Application of Graphic Recognition of the Social Network Structure of Urban Agglomeration

The spatial structure of urban agglomeration is an important branch of economic geography. As far as the current scholars’ research is concerned, the research method of urban agglomeration is relatively simple, and the visual effect of the results is poor. In this paper, the theory of social network analysis is used and the relationship within the urban agglomeration is expressed by using the UCINET6.0 and NETDRAW software. And then, the Urban Agglomeration along the middle reaches of the Yangtze River is taking as the object of empirical research. The Urban Agglomeration along the middle reaches of the Yangtze River, one of the most intensive areas of education in China, undertakes the important mission of building a new growth pole in China. However, the phenomenon of “group instead of cluster” has always been the bottleneck of besetting healthy development of the urban agglomeration, and the cluster effect appears a decreasing trend. This paper uses the modified economic gravity model and social network analysis method and constructs the “three-dimensional” diagnosis model of social network structure of urban agglomeration consisted of the primate city—social network structure density—social network structure intensity. The economic membership grade and centricity of the primate city, social network structure density of the urban agglomeration and coherent subgroup, and the social network structure intensity of the Urban Agglomeration in the middle reaches of the Yangtze River is measured. It demonstrates the spatial structure of the Urban Agglomeration along the middle reaches of the Yangtze River shows the social network structure characteristics of “weak center traction and discrete clusters”, and points out three problems restricting the Urban Agglomeration along the middle reaches of the Yangtze River. With the introduction of new theories, a three-dimensional diagnostic tool of social network structure of urban agglomerations is designed, which provides theoretical support and decision support for solving the problem of “group instead of cluster” in urban agglomeration.