Network Reconstruction and Community Detection from Dynamics

We present a scalable nonparametric Bayesian method to perform network reconstruction from observed functional behavior that at the same time infers the communities present in the network. We show that the joint reconstruction with community detection has a synergistic effect, where the edge correla...

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Bibliographic Details
Published in:Physical review letters 2019-09, Vol.123 (12), p.128301-128301, Article 128301
Main Author: Peixoto, Tiago P
Format: Article
Language:English
Subjects:
Bayesian analysis
Communities
Epidemics
Ising model
Letters
Polymer, Soft Matter, Biological, Climate, and Interdisciplinary Physics
Reconstruction
Synergistic effect
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Summary:We present a scalable nonparametric Bayesian method to perform network reconstruction from observed functional behavior that at the same time infers the communities present in the network. We show that the joint reconstruction with community detection has a synergistic effect, where the edge correlations used to inform the existence of communities are also inherently used to improve the accuracy of the reconstruction which, in turn, can better inform the uncovering of communities. We illustrate the use of our method with observations arising from epidemic models and the Ising model, both on synthetic and empirical networks, as well as on data containing only functional information.
ISSN:0031-9007
1079-7114
DOI:10.1103/physrevlett.123.128301