An Adaptive Network Model to Simulate Consensus Formation Driven by Social Identity Recognition
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 m...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/1742065 |
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| _version_ | 1850169906593529856 |
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| author | Kaiqi Zhang Zinan Lv Hai Feng Du Honghui Zou |
| author_facet | Kaiqi Zhang Zinan Lv Hai Feng Du Honghui Zou |
| author_sort | Kaiqi Zhang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-ad0b1bc3b0c54d5b9c4e0d3d6862117e |
| institution | OA Journals |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-ad0b1bc3b0c54d5b9c4e0d3d6862117e2025-08-20T02:20:37ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/17420651742065An Adaptive Network Model to Simulate Consensus Formation Driven by Social Identity RecognitionKaiqi Zhang0Zinan Lv1Hai Feng Du2Honghui Zou3School of Economy and Management, Chang’an University, Xi’an, ChinaCollege of Transportation Engineering, Chang’an University, Xi’an, ChinaCenter for Public Management and Complexity Science Research, Xi’an Jiaotong University, Xi’an, ChinaCollege of Transportation Engineering, Chang’an University, Xi’an, ChinaModels 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.http://dx.doi.org/10.1155/2020/1742065 |
| spellingShingle | Kaiqi Zhang Zinan Lv Hai Feng Du Honghui Zou An Adaptive Network Model to Simulate Consensus Formation Driven by Social Identity Recognition Complexity |
| title | An Adaptive Network Model to Simulate Consensus Formation Driven by Social Identity Recognition |
| title_full | An Adaptive Network Model to Simulate Consensus Formation Driven by Social Identity Recognition |
| title_fullStr | An Adaptive Network Model to Simulate Consensus Formation Driven by Social Identity Recognition |
| title_full_unstemmed | An Adaptive Network Model to Simulate Consensus Formation Driven by Social Identity Recognition |
| title_short | An Adaptive Network Model to Simulate Consensus Formation Driven by Social Identity Recognition |
| title_sort | adaptive network model to simulate consensus formation driven by social identity recognition |
| url | http://dx.doi.org/10.1155/2020/1742065 |
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