通过分解复杂网络对传播器进行排序
Ranking spreaders by decomposing complex networks
摘要：
对网络中节点的传播能力进行排序是一个基本问题，它涉及到信息和疾病控制等实际应用。在以前的文献中，一个网络分解过程称为k壳方法已被证明可以有效地识别最有影响力的传播者。本文发现，k壳方法在对网络中所有节点进行排序时存在一定的局限性。我们还发现，这些限制是由于在分解网络时只考虑剩余节点之间的链接（剩余度），而完全忽略了连接到删除节点的所有链接（耗尽度）。因此，我们提出了一个混合度分解（MDD）的过程中，剩余度和耗尽度都考虑。通过模拟真实网络上的流行病传播过程，我们证明了MDD方法在对传播者进行排序时的性能优于k-shell和度方法。最后讨论了网络结构对MDD方法性能的影响。
英文摘要：
Ranking the nodes' ability for spreading in networks is a fundamental problem which relates to many real applications such as information and disease control. In the previous literatures, a network decomposition procedure called k-shell method has been shown to effectively identify the most influential spreaders. In this paper, we find that the k-shell method have some limitations when it is used to rank all the nodes in the network. We also find that these limitations are due to considering only the links between the remaining nodes (residual degree) while entirely ignoring all the links connecting to the removed nodes (exhausted degree) when decomposing the networks. Accordingly, we propose a mixed degree decomposition (MDD) procedure in which both the residual degree and the exhausted degree are considered. By simulating the epidemic process on the real networks, we show that the MDD method can outperform the k-shell and the degree methods in ranking spreaders. Finally, the influence of the network structure on the performance of the MDD method is discussed.
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