Core-Intermediate-Peripheral Index: Factor Analysis of Neighborhood and Shortest Paths-based Centrality Metrics

Meghanathan, Natarajan

arXiv.org Artificial Intelligence 

The topological importance of nodes in complex networks has been analyzed in the literature from the perspectives of core-periphery structure and centrality metrics. While the core-periphery structure analysis of a network is more of a qualitative approach (and sometimes quantitative) at a mesoscopic level, centrality metrics are designed to quantify the topological importance of individual nodes in a network. The core-periphery analysis of a network is aimed at categorizing a node as either a core node or a peripheral node. The current status quo in the literature on the definitions of core nodes and peripheral nodes is that the core nodes need to be of larger degree and form a highly dense backbone to which the low degree peripheral nodes are connected to; the peripheral nodes are expected to be not connected to other peripheral nodes as well. Some of the works (e.g., [1-3]) in the literature have suggested that high degree nodes need not always be core nodes; but they still analyze the core-periphery structure and quantify the extent of coreness of a node within the realms of the above model.

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