## 2 Literature Review
### Mixing Patterns of Urban Networks  
Compared to single-type urban networks, identifying intercity connections and interactions and understanding urban evolution patterns are crucial for promoting balanced development between cities and comprehending the formation of urban agglomerations [19]. Mixing patterns is a key concept in complex network analysis, proposed by [PERSON] to measure the similarity between nodes in networks [18]. Regarding the application of mixing patterns, early scholars primarily focused on the phenomenon of \"homophily\" in social networks, where individuals tend to establish connections with others sharing similar characteristics [42]. In technological networks like the internet, these networks often exhibit scale-free characteristics [43]. In social networks, such as research collaboration and actor collaboration networks, they are often assortative [44]. With the development of network science, the concept of the mixing patterns has gradually been introduced into multiple disciplines, including economics and sociology, to analyze connection patterns in different types of networks. Thus, providing a broader perspective for understanding connection patterns in urban networks [17]. In urban network research, the application of mixing patterns not only deepens understanding of urban network structural features but also reveals connection preferences formed by the similarity or dissimilarity of node attributes, providing a theoretical foundation for understanding the evolution of urban networks and functional optimization. Existing research employs assortativity coefficients to quantitatively analyze mixing patterns in urban networks, quantifying cities' connection tendencies based on specific attributes, and finds that investment relationships in urban agglomerations tend toward central agglomeration, indicating that cities with similar attributes are more likely to form close connections, thereby influencing the organizational characteristics and internal structure of urban agglomerations [45; 46]. In migration networks, cities generally exhibit assortative characteristics, where cities tend to establish close connections with others of similar economic levels or cultural backgrounds [47; 48]. In contrast, transportation and innovation networks more often demonstrate disassortative characteristics, indicating that connections in these networks tend to link cities with significantly different attributes, thereby promoting complementarity and interconnectivity between different cities [49; 50; 51]. This is particularly evident in high-speed rail networks; developed regions demonstrate multiple-core, complex network patterns, while in developing regions, a clear core-periphery pattern emerges where central cities strengthen their connections, but peripheral cities face growing marginalization [52; 53]. Although existing research has made certain progress, current discussions on urban network mixing patterns still lack systematic analysis, particularly with limited discussion of network mixing patterns at the urban agglomeration scale. More importantly, current research primarily analyzes urban network mixing patterns from the perspective of node degree while paying less attention to mixing patterns under other structural features of urban networks, with even rarer analyses of urban agglomeration network mixing patterns based on urban socioeconomic attributes. Based on the above discussion, this study investigates mixing patterns in urban agglomerations through two dimensions: structural features and socioeconomic attributes. The structural dimension encompasses spatial configuration, transportation infrastructure, and urban hierarchies, which collectively shape the intensity and morphology of urban agglomeration processes. The economic dimension, including levels of economic development, population dynamics, and resource distribution, determines the nature of intercity interactions and cooperation mechanisms.