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Heatmap centrality: A new measure to identify super-spreader nodes in scale-free networks

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  • Christina Durón

Abstract

The identification of potential super-spreader nodes within a network is a critical part of the study and analysis of real-world networks. Motivated by a new interpretation of the “shortest path” between two nodes, this paper explores the properties of the heatmap centrality by comparing the farness of a node with the average sum of farness of its adjacent nodes in order to identify influential nodes within the network. As many real-world networks are often claimed to be scale-free, numerical experiments based upon both simulated and real-world undirected and unweighted scale-free networks are used to illustrate the effectiveness of the proposed “shortest path” based measure with regards to its CPU run time and ranking of influential nodes.

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  • Christina Durón, 2020. "Heatmap centrality: A new measure to identify super-spreader nodes in scale-free networks," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-31, July.
    • Handle: RePEc:plo:pone00:0235690
    DOI: 10.1371/journal.pone.0235690
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