社区结构揭示了复杂网络中的路径多样性
Ye Deng1,2, Jun Wu3,4, Xin Lu5
1Department of Systems Science, Faculty of Arts and Sciences, Beijing Normal University, Zhuhai, China.
Nature communications
|March 6, 2026
概括
社区结构显著影响复杂网络中的路径多样性. 这一发现揭示了一个由接口驱动的效应,它增加了最短的路径,帮助网络设计.
科学领域:
- 网络科学 网络科学
- 复杂系统分析 复杂系统分析
- 计算社会科学 计算社会科学
背景情况:
- 现实世界的网络在节点之间的最短路径中表现出显著的异质性.
- 驱动这种路径多重性的基本机制在很大程度上仍未被探索.
- 了解路径的多重性对于网络分析和优化至关重要.
研究的目的:
- 确定影响复杂网络路径多重性的关键因素.
- 介绍和分析相对路径多重性的概念.
- 开发一个复制观察到的路径多重现象的网络模型.
主要方法:
- 引入相对路径的多重度指标.
- 社区结构与路径多样性之间的相关性分析.
- 有针对性的边缘重新布线实验以验证发现.
- 基于部落结构的网络模型的开发.
主要成果:
- 社区结构与路径多重性有很强的相关性,其表现优于其他网络指标.
- 社区边界的接口驱动效应急剧增加了最短路径的数量.
- 拟议的部落结构模型成功地重现了现实世界的网络现象.
结论:
- 社区结构是复杂网络中路径多样性的主要驱动因素.
- 这些发现为路径异质性提供了一种机制性的解释.
- 这项研究对网络设计,优化和理解复杂系统有影响.
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