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@article{Arnaudon:2020:10.1103/physrevresearch.2.033104,
author = {Arnaudon, A and Peach, R and Barahona, M},
doi = {10.1103/physrevresearch.2.033104},
journal = {Physical Review Research},
title = {Scale-dependent measure of network centrality from diffusion dynamics},
url = {http://dx.doi.org/10.1103/physrevresearch.2.033104},
volume = {2},
year = {2020}
}

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TY  - JOUR
AB  - Classic measures of graph centrality capture distinct aspects of node importance, from the local (e.g., degree) to the global (e.g., closeness). Here we exploit the connection between diffusion and geometry to introduce a multiscale centrality measure. A node is defined to be central if it breaks the metricity of the diffusion as a consequence of the effective boundaries and inhomogeneities in the graph. Our measure is naturally multiscale, as it is computed relative to graph neighbourhoods within the varying time horizon of the diffusion. We find that the centrality of nodes can differ widely at different scales. In particular, our measure correlates with degree (i.e., hubs) at small scales and with closeness (i.e., bridges) at large scales, and also reveals the existence of multi-centric structures in complex networks. By examining centrality across scales, our measure thus provides an evaluation of node importance relative to local and global processes on the network.
AU  - Arnaudon,A
AU  - Peach,R
AU  - Barahona,M
DO  - 10.1103/physrevresearch.2.033104
PY  - 2020///
SN  - 2643-1564
TI  - Scale-dependent measure of network centrality from diffusion dynamics
T2  - Physical Review Research
UR  - http://dx.doi.org/10.1103/physrevresearch.2.033104
UR  - http://arxiv.org/abs/1907.08624v1
UR  - http://hdl.handle.net/10044/1/80530
VL  - 2
ER  -

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