An Adaptive Network Model to Simulate Consensus Formation Driven by Social Identity Recognition. (8th October 2020)

• Record Type: Journal Article
• Authors: Zhang, Kaiqi; Lv, Zinan; Du, Hai Feng; Zou, Honghui
• Other Names: Chen Hongshu Academic Editor.
• Is Part Of: Complexity. Volume 2020(2020)
• Publication Date: 2020-10-08
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2020/1742065
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : Models of the consensus of the individual state in social systems have been the subject of recent research studies in the physics literature. We investigate how network structures coevolve with the individual state under the framework of social identity theory. Also, we propose an adaptive network model to achieve state consensus or local structural adjustment of individuals by evaluating the homogeneity among them. Specifically, the similarity threshold significantly affects the evolution of the network with different initial conditions, and thus there emerges obvious community structure and polarization. More importantly, there exists a critical point of phase transition, at which the network may evolve into a significant community structure and state-consistent group.