Department of Agricultural and Rural Policy Research, Korea Rural Economic Institute, Naju-si, Jeollanam-do, Republic of Korea.
Department of Agricultural Economics, Sociology, and Education, Pennsylvania State University, University Park, Pennsylvania, United States of America.
PLoS One. 2019 Jul 24;14(7):e0220295. doi: 10.1371/journal.pone.0220295. eCollection 2019.
Recent years have seen tremendous advances in the scientific study of networks, as more and larger data sets of relationships among nodes have become available in many different fields. This has led to pathbreaking discoveries of near-universal network behavior over time, including the principle of preferential attachment and the emergence of scaling in complex networks. Missing from the set of network analysis methods to date is a measure that describes for each node how its relationship (or links) with other nodes changes from one period to the next. Conventional measures of network change for the most part show how the degrees of a node change; these are scalar comparisons. Our contribution is to use, for the first time, the cosine similarity to capture not just the change in degrees of a node but its relationship to other nodes. These are vector (or matrix)-based comparisons, rather than scalar, and we refer to them as "rewiring" coefficients. We apply this measure to three different networks over time to show the differences in the two types of measures. In general, bigger increases in our rewiring measure are associated with larger increases in network density, but this is not always the case.
近年来，随着越来越多的不同领域的节点间关系数据集变得可用，网络的科学研究取得了巨大的进展。这导致了突破性的发现，即随着时间的推移，网络行为具有近乎普遍的规律，包括优先连接原则和复杂网络中的标度出现。迄今为止，网络分析方法中缺少一种度量标准，该标准可以描述每个节点的关系（或链接）如何从一个时期到下一个时期发生变化。网络变化的常规度量标准在大多数情况下显示的是节点的度如何变化；这些是标量比较。我们的贡献是首次使用余弦相似度来捕捉节点的度变化，以及它与其他节点的关系。这些是基于向量（或矩阵）的比较，而不是标量，我们称之为“重连”系数。我们将该度量标准应用于三个不同的随时间变化的网络，以显示两种度量标准的差异。一般来说，我们的重连度量标准的较大增加与网络密度的较大增加相关，但情况并非总是如此。
