Structure Balance and Opinions Dynamic in Signed Social Network

In this paper, the authors consider both the nodes' opinions dynamics and signed network edges' evolution. Simulated Annealing Algorithm is applied for searching the minimal global energy function, and bounded confidence model is used for nodes' opinions updating. The authors find that the local and global level of balance of signed network is consistent with collective opinions 2-polarization. This property is explainable in terms of the structure balance of the sign distributions on the nodes and edges. The level of balance and the final opinions polarization pattern are achieved depends on the initial density of signed network, and the percentage of initial positive edges. Numerical simulations of the proposed model display a rich and intuitive behavior of the opinions polarization processes. In particular, the authors show that opinions persistent fluctuations is consistent with minimal global the energy function. This work verify that signed social networks are indeed limited balanced, could be used to explain ubiquitous binary polarization phenomenon of real world.