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原文連結
論文資訊
- 類型：已發表論文
- 日期：2016-08-18
摘要
We introduce a 網絡 statistic that measures structural properties at the micro-, meso-, and macroscopic scales, while still being easy to compute and interpretable at a glance. Our statistic, the onion spectrum, is based on the onion decomposition, which refines the k-core decomposition, a standard 網絡 fingerprinting method. The onion spectrum is exactly as easy to compute as the k-cores: It is based on the stages at which each vertex gets removed from a graph in the standard algorithm for computing the k-cores. Yet, the onion spectrum reveals much more 資訊 about a 網絡, and at multiple scales; for example, it can be used to quantify node heterogeneity, degree correlations, centrality, and tree-or lattice-likeness. Furthermore, unlike the k-core decomposition, the combined degree-onion spectrum
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