Network Catastrophe: Self-Organized Patterns Reveal both the Instability and the Structure of Complex Networks
Network Catastrophe: Self-Organized Patterns Reveal both the Instability and the Structure of Complex Networks
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DOI：
10.1038/srep09450
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发表时间：
2015-03-30
影响因子：
4.6
通讯作者：
Lu, Tsai-Ching
中科院分区：
文献类型：
--
作者：
Moon, Hankyu;Lu, Tsai-Ching
社会或生物系统中的关键事件可以理解为由于稳定性恶化而产生的大规模自我涌现现象。在这些事件发生之前，我们经常观察到一些特殊的模式，这就提出了一个问题——如何解释这些自组织模式，从而更多地了解即将到来的危机。我们从一个非常一般的描述开始——相互作用的群体产生了大规模的紧急行为，构成了关键事件。然后我们提出了一个关键问题：在互动网络和涌现模式之间是否存在可量化的关系？我们的调查使我们对以下问题有了基本的认识：基于模式动力学的主模检测系统的过渡；2. 根据观察到的模式确定其不断变化的结构。本研究的主要发现是，虽然模式被相互作用网络扭曲，但即使网络不断演变，其主模式对扭曲也是不变的。我们对现实世界市场的分析显示，在关键转变（如房地产市场崩溃和股市崩溃）附近，常见的自组织行为是有可能的，因此，在关键事件全面发生之前，我们就可以检测到它们。
Critical events in society or biological systems can be understood as large-scale self-emergent phenomena due to deteriorating stability. We often observe peculiar patterns preceding these events, posing a question of-how to interpret the self-organized patterns to know more about the imminent crisis. We start with a very general description - of interacting population giving rise to large-scale emergent behaviors that constitute critical events. Then we pose a key question: is there a quantifiable relation between the network of interactions and the emergent patterns? Our investigation leads to a fundamental understanding to: 1. Detect the system's transition based on the principal mode of the pattern dynamics; 2. Identify its evolving structure based on the observed patterns. The main finding of this study is that while the pattern is distorted by the network of interactions, its principal mode is invariant to the distortion even when the network constantly evolves. Our analysis on real-world markets show common self-organized behavior near the critical transitions, such as housing market collapse and stock market crashes, thus detection of critical events before they are in full effect is possible.