网络演化中簇和突发的自然涌现
Natural emergence of clusters and bursts in network evolution
摘要：
具有优先连接的网络模型，其中新节点被注入到网络中，并与现有节点形成与其当前连接成比例的链接，已经研究了一段时间。已经引入了扩展，其中节点按比例连接到任意适应度函数。然而，在这些模型中，连接到一个节点总是增加该节点在未来获得更多链接的能力。我们研究网络的增长，其中节点按比例连接到现有节点的聚类系数，或三角形的局部密度。与偏好连接或富-更富模型相比，连接到节点通常会降低其聚类系数。这种简单的修改自然会导致各种丰富的现象，包括老化，非泊松突发动力学和社区形成。这个理论模型表明，复杂的网络结构可以生成，而不人为地施加多个动力学机制，并可能揭示潜在的忽视机制存在于复杂系统。
英文摘要：
Network models with preferential attachment, where new nodes are injected into the network and form links with existing nodes proportional to their current connectivity, have been well studied for some time. Extensions have been introduced where nodes attach proportionally to arbitrary fitness functions. However, in these models, attaching to a node always increases the ability of that node to gain more links in the future. We study network growth where nodes attach proportionally to the clustering coefficients, or local densities of triangles, of existing nodes. Attaching to a node typically lowers its clustering coefficient, in contrast to preferential attachment or rich-get-richer models. This simple modification naturally leads to a variety of rich phenomena, including aging, non-Poissonian bursty dynamics, and community formation. This theoretical model shows that complex network structure can be generated without artificially imposing multiple dynamical mechanisms and may reveal potentially overlooked mechanisms present in complex systems.
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