Empirical research on evolutionary behavior of covert network with preference measurement

A key ingredient of studying the topological evolution of covert network is the individual behaviors which generate the evolutionary dynamics of covert organizational network. In this paper, we proposed an improved preference measurement method and used it to analyze three evolutionary behaviors of a real covert network, namely node addition, node deletion and link formation. Simulation experiment demonstrated that the improved method is robust on the small organizational network. The empirical study showed the specific pattern of evolutionary behaviors by offering direct quantitative support from preferential measurement. The measured property is then extended from degree to multiple node properties. The results indicate that the preferences of different behaviors follow different distributions with linear or nonlinear tendency across the process according to the type of node property. We conclude that the general scale-free network model is not suitable to model the evolutionary process of covert network.