Abstract
The decay centrality (DEC) metric for a vertex weighs the distance of the vertex to the rest of the vertices on the basis of a decay parameter (0 < δ < 1). In this paper, we analyze a suite of 48 real-world networks and compute the DEC values for δ values ranging from 0.01 to 0.99 for each of these networks. We explore the presence of a particular or range of δ values within which there is a very strong positive correlation (Pearson’s correlation coefficient of 0.8 or above) between DEC and each of the four commonly studied centrality metrics: degree centrality (DEG), eigenvector centrality (EVC), betweenness centrality (BWC) and closeness centrality (CLC). We observe 0.01 to be the most appropriate δ value for which there exists a very strong positive correlation between DEC and each of DEG, EVC and BWC for at least 50% of the networks.
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Acknowledgments
The research is financed by the NASA EPSCoR sub award (#: NNX14AN38A) from University of Mississippi.
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Meghanathan, N. (2017). Correlation Analysis of Decay Centrality. In: Silhavy, R., Senkerik, R., Kominkova Oplatkova, Z., Prokopova, Z., Silhavy, P. (eds) Cybernetics and Mathematics Applications in Intelligent Systems. CSOC 2017. Advances in Intelligent Systems and Computing, vol 574. Springer, Cham. https://doi.org/10.1007/978-3-319-57264-2_41
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DOI: https://doi.org/10.1007/978-3-319-57264-2_41
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