Consensus reaching in social network DeGroot Model: The roles of the Self-confidence and node degree
Consensus reaching in social network DeGroot Model: The roles of the Self-confidence and node degree
复制标题
社交网络 DeGroot 模型中的共识达成：自信心和节点度的作用
DOI：
10.1016/j.ins.2019.02.028
复制
发表时间：
2019-06-01
影响因子：
8.1
通讯作者：
Herrera, Francisco
中科院分区：
文献类型：
--
作者：
Ding, Zhaogang;Chen, Xia;Herrera, Francisco
本文研究了在社会网络DeGroot模型中，智能体的自信心水平和节点程度对共识意见形成和共识收敛速度的影响。我们发现：(1)较高的自信心会增加主体决定共识意见的重要程度，但也会减缓所有主体能够获得共识的收敛速度；(2)有利于加快收敛速度，能够达成所有主体能够在社会网络中平衡自信水平和节点度的共识。(C)2019 Elsevier Inc.保留所有权利。
In this paper, we investigate how the agent's self-confidence level and the node degree influence the consensus opinion formation and the consensus convergence speed in the social network DeGroot model. We find that (1) the higher self-confidence will increase the agent's importance degree to determine the consensus opinion, but will also slow down the convergence speed for all agents to be able to obtain consensus, and (2) it is conducive to accelerating the convergence speed to be able to reach a consensus where all agents can manage to balance self-confidence levels and node degrees in the social network. (C) 2019 Elsevier Inc. All rights reserved.