Research on Social Network Clustering Synchronization Based on Improved Coupling Time-Delay Complex Network Synchronization Model

Abstract

In order to study the synchronous evolution of social networks and the process of reaching consensus, the coupled time-delay complex network model is improved. Aiming at the problem of constant coupling delay in the original model, a random coupling delay rule is proposed to adjust the network evolution rate. Aiming at the same importance of nodes in the original model, the multi-attribute decision method is introduced to change the importance of nodes and optimize the efficiency of network synchronization. Based on Lyapunov stability theory and matrix theory, the conditions for social networks to achieve cluster synchronization are deduced. Finally, the evolution experiment is carried out with Twitter social network data set, which verifies the theoretical feasibility and effectiveness.