参与者不变,在动态网络中不断变化的影响模式.
Shaojie Min1, Jiaxing Shang2, Ji Liu2
1Fudan University, Shanghai Key Lab of Intelligent Information Processing, College of Computer Science and Artificial Intelligence, Shanghai 200433, China.
Physical review. E
|December 23, 2025
概括
动态网络影响模式令人惊地一致,通常只能通过一个核心模式来解释. 这一发现简化了复杂系统的分析,并揭示了异质节点参与.
科学领域:
- 复杂系统科学 复杂系统科学
- 网络科学 网络科学
- 数据科学数据科学数据科学
背景情况:
- 了解动态网络中的影响演变是复杂系统的关键.
- 由于感知到的分析复杂性,时间影响模式未被充分探索.
- 现实世界的网络在分析许多不断变化的影响过程时存在挑战.
研究的目的:
- 在动态网络影响中发现参与者不变特征.
- 为了证明少量影响模式可以代表网络行为.
- 为理解复杂系统中的影响进化提供一个框架.
主要方法:
- 分析了来自不同领域的50个动态网络数据集.
- 识别网络中的核心影响模式.
- 使用关联权重对节点参与的量化.
主要成果:
- 少数影响模式 (通常只有一个) 捕捉整体网络行为.
- 影响模式显示了同一类别的网络之间的相似性.
- 节点重量分布遵循一个功率定律,表明异质参与.
结论:
- 动态网络影响表现出参与者不变的特征.
- 可实现动态网络的简化表示.
- 提供了对异质节点参与和影响演变的洞察.
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