Highly Clustered Complex Networks in the Configuration Model: Random Regular Small-World Network
| Autor: | Unjong Yu, Wonhee Jeong, Hoseung Jang |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Physics - Physics and Society
Small-world network Degree (graph theory) Statistical Mechanics (cond-mat.stat-mech) Computer science Social connectedness General Physics and Astronomy FOS: Physical sciences Percolation threshold Physics and Society (physics.soc-ph) Complex network Topology 01 natural sciences 010305 fluids & plasmas 0103 physical sciences 010306 general physics Cluster analysis Condensed Matter - Statistical Mechanics Clustering coefficient |
| DOI: | 10.48550/arxiv.1911.11910 |
| Popis: | We propose a method to make a highly clustered complex network within the configuration model. Using this method, we generated highly clustered random regular networks and analyzed the properties of them. We show that highly clustered random regular networks with appropriate parameters satisfy all the conditions of the small-world network: connectedness, high clustering coefficient, and small-world effect. We also study how clustering affects the percolation threshold in random regular networks. In addition, the prisoner's dilemma game is studied and the effects of clustering and degree heterogeneity on the cooperation level are discussed. Comment: 6 pages, 5 figures |
| Databáze: | OpenAIRE |
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