Literature DB >> 20866285

Small-world behavior in time-varying graphs.

J Tang1, S Scellato, M Musolesi, C Mascolo, V Latora.   

Abstract

Connections in complex networks are inherently fluctuating over time and exhibit more dimensionality than analysis based on standard static graph measures can capture. Here, we introduce the concepts of temporal paths and distance in time-varying graphs. We define as temporal small world a time-varying graph in which the links are highly clustered in time, yet the nodes are at small average temporal distances. We explore the small-world behavior in synthetic time-varying networks of mobile agents and in real social and biological time-varying systems.

Mesh:

Year:  2010        PMID: 20866285     DOI: 10.1103/PhysRevE.81.055101

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  32 in total

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4.  A dynamical systems view of network centrality.

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5.  Dynamic graph metrics: Tutorial, toolbox, and tale.

Authors:  Ann E Sizemore; Danielle S Bassett
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6.  Temporal exponential random graph models of longitudinal brain networks after stroke.

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7.  Analysis of complexity and dynamic functional connectivity based on resting-state EEG in early Parkinson's disease patients with mild cognitive impairment.

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8.  Sparse matrix computations for dynamic network centrality.

Authors:  Francesca Arrigo; Desmond J Higham
Journal:  Appl Netw Sci       Date:  2017-06-24

9.  Synchronization dynamics and evidence for a repertoire of network states in resting EEG.

Authors:  Richard F Betzel; Molly A Erickson; Malene Abell; Brian F O'Donnell; William P Hetrick; Olaf Sporns
Journal:  Front Comput Neurosci       Date:  2012-09-28       Impact factor: 2.380

10.  Emergence of network features from multiplexity.

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Journal:  Sci Rep       Date:  2013       Impact factor: 4.379

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