Topological Strata of Weighted Complex Networks.

The statistical mechanical approach to complex networks is the dominant paradigm in describing natural and societal complex systems. The study of network properties, and their implications on dynamical processes, mostly focus on locally defined quantities of nodes and edges, such as node degrees, ed...

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Main Authors: Giovanni Petri, Martina Scolamiero, Irene Donato, Francesco Vaccarino
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2013-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3689815?pdf=render
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spelling doaj-c10d2380569140fe88cd0100d38b89132020-11-25T02:19:48ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-0186e6650610.1371/journal.pone.0066506Topological Strata of Weighted Complex Networks.Giovanni PetriMartina ScolamieroIrene DonatoFrancesco VaccarinoThe statistical mechanical approach to complex networks is the dominant paradigm in describing natural and societal complex systems. The study of network properties, and their implications on dynamical processes, mostly focus on locally defined quantities of nodes and edges, such as node degrees, edge weights and -more recently- correlations between neighboring nodes. However, statistical methods quickly become cumbersome when dealing with many-body properties and do not capture the precise mesoscopic structure of complex networks. Here we introduce a novel method, based on persistent homology, to detect particular non-local structures, akin to weighted holes within the link-weight network fabric, which are invisible to existing methods. Their properties divide weighted networks in two broad classes: one is characterized by small hierarchically nested holes, while the second displays larger and longer living inhomogeneities. These classes cannot be reduced to known local or quasilocal network properties, because of the intrinsic non-locality of homological properties, and thus yield a new classification built on high order coordination patterns. Our results show that topology can provide novel insights relevant for many-body interactions in social and spatial networks. Moreover, this new method creates the first bridge between network theory and algebraic topology, which will allow to import the toolset of algebraic methods to complex systems.http://europepmc.org/articles/PMC3689815?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Giovanni Petri
Martina Scolamiero
Irene Donato
Francesco Vaccarino
spellingShingle Giovanni Petri
Martina Scolamiero
Irene Donato
Francesco Vaccarino
Topological Strata of Weighted Complex Networks.
PLoS ONE
author_facet Giovanni Petri
Martina Scolamiero
Irene Donato
Francesco Vaccarino
author_sort Giovanni Petri
title Topological Strata of Weighted Complex Networks.
title_short Topological Strata of Weighted Complex Networks.
title_full Topological Strata of Weighted Complex Networks.
title_fullStr Topological Strata of Weighted Complex Networks.
title_full_unstemmed Topological Strata of Weighted Complex Networks.
title_sort topological strata of weighted complex networks.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2013-01-01
description The statistical mechanical approach to complex networks is the dominant paradigm in describing natural and societal complex systems. The study of network properties, and their implications on dynamical processes, mostly focus on locally defined quantities of nodes and edges, such as node degrees, edge weights and -more recently- correlations between neighboring nodes. However, statistical methods quickly become cumbersome when dealing with many-body properties and do not capture the precise mesoscopic structure of complex networks. Here we introduce a novel method, based on persistent homology, to detect particular non-local structures, akin to weighted holes within the link-weight network fabric, which are invisible to existing methods. Their properties divide weighted networks in two broad classes: one is characterized by small hierarchically nested holes, while the second displays larger and longer living inhomogeneities. These classes cannot be reduced to known local or quasilocal network properties, because of the intrinsic non-locality of homological properties, and thus yield a new classification built on high order coordination patterns. Our results show that topology can provide novel insights relevant for many-body interactions in social and spatial networks. Moreover, this new method creates the first bridge between network theory and algebraic topology, which will allow to import the toolset of algebraic methods to complex systems.
url http://europepmc.org/articles/PMC3689815?pdf=render
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