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Centrality Analysis of the United States Network Graph

Centrality Analysis of the United States Network Graph
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Author(s): Natarajan Meghanathan (Jackson State University, USA)
Copyright: 2019
Pages: 12
Source title: Advanced Methodologies and Technologies in Network Architecture, Mobile Computing, and Data Analytics
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-5225-7598-6.ch023

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Abstract

The authors model the contiguous states (48 states and the District of Columbia) of the United States (US) as an undirected network graph with each state represented as a node and there is an edge between two nodes if the corresponding two states share a common border. They determine a ranking of the states in the US with respect to the four commonly studied centrality metrics: degree, eigenvector, betweenness, and closeness. They observe the states of Missouri and Maine to be, respectively, the most central state and the least central state with respect to all the four centrality metrics. The degree distribution is bi-modal Poisson. The eigenvector and closeness centralities also exhibit Poisson distribution, while the betweenness centrality exhibits power-law distribution. The authors observe a higher correlation in the ranking of vertices based on the degree centrality and betweenness centrality.

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