Consensus Convergence Speed in Social Network DeGroot Model: The Effects of the Agents With High Self-Confidence Levels

Abstract

In group decision making (GDM), opinion dynamics is a useful tool to investigate consensus formation. Notably, consensus convergence speed is of key importance to manage the consensus formation in GDM with opinion dynamics. Recently, social network DeGroot (SNDG) model has been widely used in opinion dynamics. Based on this, this article dedicates to study how agents’ high self-confidence levels affect the consensus convergence speed in SNDG model. Interestingly, using theoretical analysis, we prove that: 1) the speed of consensus reaching is subject to the largest self-confidence level of opinion followers and 2) the speed of consensus reaching is also subject to the top two self-confidence levels of opinion leaders. Furthermore, through extensive simulation’, we find that the theoretical results are robust to the topological structure and the size of social networks.