Knowledge network has been widely used in many fields of library and information science because of its advantages of presenting and revealing knowledge correlations. The patterns and laws in the process of dynamic evolution of knowledge networks have become the focus of library and information science academic community. With the theory and method of complex networks, this article constructed time-series domain knowledge networks. From the network macro-structure characteristics, underlying topology and hub nodes, the dynamic analysis of the structural stability and knowledge emergence in the process of knowledge network evolution is carried out. The results show that the knowledge networks exhibit a stable scale-free network feature, when the networks evolve into maturity; Underlying blocks and network node scale have better fitting effect at the maturity stage and the block subgraph concentration is stable; Hub node members are more stable and emerge as domain core knowledge during the mature stage of the network.