Dynamical Systems to Monitor Complex Networks in Continuous Time

In many settings it is appropriate to treat the evolution of pairwise interactions over continuous time. We show that new Katz-style centrality measures can be derived in this context via solutions to a nonautonomous ODE driven by the network dynamics. This allows us to identify and track, at any re...

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Main Authors: Grindrod, P, Higham, D
Format: Journal article
Published: 2013
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author Grindrod, P
Higham, D
author_facet Grindrod, P
Higham, D
author_sort Grindrod, P
collection OXFORD
description In many settings it is appropriate to treat the evolution of pairwise interactions over continuous time. We show that new Katz-style centrality measures can be derived in this context via solutions to a nonautonomous ODE driven by the network dynamics. This allows us to identify and track, at any resolution, the most influential nodes in terms of broadcasting and receiving information through time dependent links. In addition to the classical notion of attenuation across edges used in the static Katz centrality measure, the ODE also allows for attenuation over time, so that real time "running measures" can be computed. With regard to computational efficiency, we explain why it is cheaper to track good receivers of information than good broadcasters. We illustrate the new measures on a large scale voice call network, where key features are discovered that are not evident from snapshots or aggregates.
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spelling oxford-uuid:c9550f58-da65-40ec-b074-4f6e610aa6072022-03-27T06:58:23ZDynamical Systems to Monitor Complex Networks in Continuous TimeJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:c9550f58-da65-40ec-b074-4f6e610aa607Symplectic Elements at Oxford2013Grindrod, PHigham, DIn many settings it is appropriate to treat the evolution of pairwise interactions over continuous time. We show that new Katz-style centrality measures can be derived in this context via solutions to a nonautonomous ODE driven by the network dynamics. This allows us to identify and track, at any resolution, the most influential nodes in terms of broadcasting and receiving information through time dependent links. In addition to the classical notion of attenuation across edges used in the static Katz centrality measure, the ODE also allows for attenuation over time, so that real time "running measures" can be computed. With regard to computational efficiency, we explain why it is cheaper to track good receivers of information than good broadcasters. We illustrate the new measures on a large scale voice call network, where key features are discovered that are not evident from snapshots or aggregates.
spellingShingle Grindrod, P
Higham, D
Dynamical Systems to Monitor Complex Networks in Continuous Time
title Dynamical Systems to Monitor Complex Networks in Continuous Time
title_full Dynamical Systems to Monitor Complex Networks in Continuous Time
title_fullStr Dynamical Systems to Monitor Complex Networks in Continuous Time
title_full_unstemmed Dynamical Systems to Monitor Complex Networks in Continuous Time
title_short Dynamical Systems to Monitor Complex Networks in Continuous Time
title_sort dynamical systems to monitor complex networks in continuous time
work_keys_str_mv AT grindrodp dynamicalsystemstomonitorcomplexnetworksincontinuoustime
AT highamd dynamicalsystemstomonitorcomplexnetworksincontinuoustime