Abstract: With the deepening of research on complex networks, social network modeling has become one of research hotspots. Based on Holme and Kim (HK) model, we put forward an improved HK social network model. We not only consider “preference connections” and “triangular structures”, but also consider two network growth patterns named “internal evolution” and “external extension” when adding new nodes in the network. A creative way of network dynamic evolution including nodes saturation and links refreshing is put forward based on traditional one-way growth network. The simulation results show that the improved model has power-law degree distribution, larger clustering coefficient and smaller average shortest path which satisfies small-world effects and scale-free properties at the same time. The whole social network model is spiraling in the process of link building and blocking and reproduces characteristics of real social network better.

Key words: complex network, HK model, network evolution, degree distribution, clustering coefficient