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原文連結
論文資訊
- 類型：已發表論文
- 日期：2017
摘要
Numerous centrality measures have been developed to quantify the importances of nodes in time-independent 網絡s, and many of them can be expressed as the leading eigenvector of some matrix. With the increasing availability of 網絡 data that changes in time, it is important to extend such eigenvector-based centrality measures to time-dependent 網絡s. In this paper, we introduce a principled generalization of 網絡 centrality measures that is valid for any eigenvectorbased centrality. We consider a temporal 網絡 with N nodes as a sequence of T layers that describe the 網絡 during different time windows, and we couple centrality matrices for the layers into a supracentrality matrix of size NT x NT whose dominant eigenvector gives the centrality of each node i at each time t. We refer to this eigenvector a
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