### Study on Quantity?of Echo Chambers Formed in Social Networks Based on Constraint of Dunbar’s Number

SHEN Hongyang, ZHANG Dongge, LIANG Xuefeng, MAO Tengjiao, NIU Yanjie

1. College of Command and Control Engineering, The Army Engineering University of PLA, Nanjing 210007, China
• Online:2019-09-01 Published:2019-08-30

### 邓巴数限制下的社交网络回音室数量研究

1. 中国人民解放军陆军工程大学 指挥控制工程学院，南京 210007

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.