A split-and-transfer flow based entropic centrality
Author(s) -
Frédérique Oggier,
Silivanxay Phetsouvanh,
Anwitaman Datta
Publication year - 2019
Publication title -
peerj computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.806
H-Index - 24
ISSN - 2376-5992
DOI - 10.7717/peerj-cs.220
Subject(s) - centrality , subnetwork , katz centrality , node (physics) , computer science , flow (mathematics) , set (abstract data type) , computation , flow network , network theory , network controllability , transfer (computing) , interpretation (philosophy) , network science , theoretical computer science , betweenness centrality , mathematical optimization , algorithm , mathematics , complex network , computer network , physics , combinatorics , world wide web , geometry , quantum mechanics , parallel computing , programming language
The notion of entropic centrality measures how central a node is in terms of how uncertain the destination of a flow starting at this node is: the more uncertain the destination, the more well connected and thus central the node is deemed. This implicitly assumes that the flow is indivisible, and at every node, the flow is transferred from one edge to another. The contribution of this paper is to propose a split-and-transfer flow model for entropic centrality, where at every node, the flow can actually be arbitrarily split across choices of neighbours. We show how to map this to an equivalent transfer entropic centrality set-up for the ease of computation, and carry out three case studies (an airport network, a cross-shareholding network and a Bitcoin transactions subnetwork) to illustrate the interpretation and insights linked to this new notion of centrality.
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