Based on the multi-index data of 23 cities charactered by Airport-type national logistics hub, this paper analyzes the aviation logistics spatial correlation degree, correlation network spatial structure and influencing factors of 23 cities by employing the modified Gravity Model and Social Network Analysis (SNA). The results show that: presenting a spatial correlation pattern of "dense East and sparse West, strong East and weak West" among 23 cities; the density of aviation logistics correlation network is high, the "core-semi-periphery-periphery" structure of the network is remarkable, and the "multi-center drive" situation is gradually forming, but the spatial structure is unstable; the “hub-and-spoke” hierarchical structure of the network is not obvious, and the "bridge" city has not fully played its role; there are roughly four of cohesion subgroups with different functions and the degree of faction between which is very small, the subgroup structure and gradient collaboration relationship are not reasonable; factors such as the level of economic development, the degree of opening up, the industrial structure, and the accessibility of transportation have driven the optimization and reorganization of the aviation logistics correlation network.