时间依赖复杂网络的动力学模型
A dynamic model of time-dependent complex networks
摘要：
在静态或缓慢演化的复杂网络中，“最连通”节点的特征有助于理解和预测社会、生物和技术网络系统的行为，包括它们对故障的鲁棒性、对蓄意攻击的脆弱性和扩散特性。然而，最近对大型动态网络（其特征是连接不规则且发展迅速）的实证研究表明，节点的度中心性随时间的推移几乎没有连续性，即使它们的度分布遵循幂律。这种意想不到的动态中心性表明，这些系统中的连接不是由优先连接或其他已知机制驱动的。我们提出了一种新的方法来解释现实世界的动态网络和定性重现这些动态中心现象。这种方法是基于一个动态的优先连接机制，它表现出一个急剧的过渡，从一个基地纯随机游走计划。
英文摘要：
The characterization of the "most connected" nodes in static or slowly evolving complex networks has helped in understanding and predicting the behavior of social, biological, and technological networked systems, including their robustness against failures, vulnerability to deliberate attacks, and diffusion properties. However, recent empirical research of large dynamic networks (characterized by connections that are irregular and evolve rapidly) has demonstrated that there is little continuity in degree centrality of nodes over time, even when their degree distributions follow a power law. This unexpected dynamic centrality suggests that the connections in these systems are not driven by preferential attachment or other known mechanisms. We present a novel approach to explain real-world dynamic networks and qualitatively reproduce these dynamic centrality phenomena. This approach is based on a dynamic preferential attachment mechanism, which exhibits a sharp transition from a base pure random walk scheme.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
