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在时间网络中测量社会流动性
Matthew Russell Barnes1, Vincenzo Nicosia2, Richard G Clegg3
1School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK. matthew.barnes@qmul.ac.uk.
Scientific reports
|February 18, 2025
概括
复杂的网络往往表现出"变富变富"的效应. 我们引入了层次移动性来衡量节点的成功如何随着时间的推移而变化,揭示了网络动态.
科学领域:
- 网络科学 网络科学
- 复杂系统分析 复杂系统分析
- 时间网络动力学
背景情况:
- 这是一个很棒的节目,这是一个很棒的节目.
- 富有-变得更富有-变得更富有
- 这种高度连接的节点获得更多连接的现象在复杂网络中很常见.
- 静态网络分析经常忽视节点程度演变的时间方面.
- 现有的模型,如偏好的依恋和富人俱乐部效应,分析静态快照.
研究的目的:
- 在复杂网络中引入和定义节点成功传播的时间尺度.
- 开发一种"层次移动"概念,以跟踪节点度变化的变化,随着时间的推移获得倾向.
- 为网络分析创建时间相关统计 (流动性,慈善事业,社区) 的分类.
主要方法:
- 根据跨时间段的节点度变化定义和计算"层次移动性".
- 引入时间相关统计:流动性,慈善事业和社区.
- 将这些统计数据应用于26个现实世界的时间网络和人工网络模型.
主要成果:
- 大多数分析的网络都显示出各个节点及其邻近的稳定等级位置随着时间的推移.
- 在单个节点的成功与邻近的成功之间观察到较低的相关效应.
- 移动性分类学有效地区分来自不同科学领域的网络.
结论:
- 测量层次移动性为时间网络的基础结构动态提供了有价值的见解.
- "富人变得更富"效应的相反,需要在网络中的程度不平等.
- 对网络演变的时间分析提供了比静态快照更细致的理解.
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