关键词: 观点动力学, 社交网络, 网络生成算法, 回音室, 邓巴数

Abstract: A large number of studies have found that the social network structure has a significant influence on the dynamic characteristics which occur on itself. The DNCSN（Social Network Generation Algorithm with the Constraint of Dunbar’s Number） proposed in this paper has a small average distance and a large clustering coefficient, and can generate results close to the real network on the nonlinear relationship between the degree and strength of nodes. It can be more effective to study on the characteristics of opinion evolution based on DNCSN. This paper compares the changes in the number of echo chambers formed in different network conditions by adjusting the opinion “firmness” and opinion confidence threshold parameters of each individual in the social network. The results show that when the initial opinion of the network is evenly distributed and the size of network is less than Dunbar’s number, the structure of DNCSN can reduce the number of echo chambers, compared with fully connected network of the same size, within the range of the confidence threshold is larger than 0.15. When the scale of network increases, the DNCSN can form more echo chambers than fully connected network. When the range of the confidence threshold is less than 0.1, the scale of fully connected network will affect the quantity of echo chambers and the smaller the network size is, the smaller the number of echo chambers will be.

Key words: opinion dynamics, social network, network generation algorithm, echo chambers, Dunbar’s number