Low-Temperature Behaviour of Social and Economic Networks

Real-world social and economic networks typically display a number of particular topological properties, such as a giant connected component, a broad degree distribution, the small-world property and the presence of communities of densely interconnected nodes. Several models, including ensembles of...

Full description

Bibliographic Details
Main Authors: Guido Caldarelli, Diego Garlaschelli, Thomas M. A. Fink, Sebastian E. Ahnert
Format: Article
Language:English
Published: MDPI AG 2013-08-01
Series:Entropy
Subjects:
Online Access:http://www.mdpi.com/1099-4300/15/8/3148
id doaj-acd951ef3079498089aed6b5d5b059b6
record_format Article
spelling doaj-acd951ef3079498089aed6b5d5b059b62020-11-25T00:16:52ZengMDPI AGEntropy1099-43002013-08-011583148316910.3390/e15083238Low-Temperature Behaviour of Social and Economic NetworksGuido CaldarelliDiego GarlaschelliThomas M. A. FinkSebastian E. AhnertReal-world social and economic networks typically display a number of particular topological properties, such as a giant connected component, a broad degree distribution, the small-world property and the presence of communities of densely interconnected nodes. Several models, including ensembles of networks, also known in social science as Exponential Random Graphs, have been proposed with the aim of reproducing each of these properties in isolation. Here, we define a generalized ensemble of graphs by introducing the concept of graph temperature, controlling the degree of topological optimization of a network. We consider the temperature-dependent version of both existing and novel models and show that all the aforementioned topological properties can be simultaneously understood as the natural outcomes of an optimized, low-temperature topology. We also show that seemingly different graph models, as well as techniques used to extract information from real networks are all found to be particular low-temperature cases of the same generalized formalism. One such technique allows us to extend our approach to real weighted networks. Our results suggest that a low graph temperature might be a ubiquitous property of real socio-economic networks, placing conditions on the diffusion of information across these systems.http://www.mdpi.com/1099-4300/15/8/3148complex networksgraph ensemblesgraph temperature
collection DOAJ
language English
format Article
sources DOAJ
author Guido Caldarelli
Diego Garlaschelli
Thomas M. A. Fink
Sebastian E. Ahnert
spellingShingle Guido Caldarelli
Diego Garlaschelli
Thomas M. A. Fink
Sebastian E. Ahnert
Low-Temperature Behaviour of Social and Economic Networks
Entropy
complex networks
graph ensembles
graph temperature
author_facet Guido Caldarelli
Diego Garlaschelli
Thomas M. A. Fink
Sebastian E. Ahnert
author_sort Guido Caldarelli
title Low-Temperature Behaviour of Social and Economic Networks
title_short Low-Temperature Behaviour of Social and Economic Networks
title_full Low-Temperature Behaviour of Social and Economic Networks
title_fullStr Low-Temperature Behaviour of Social and Economic Networks
title_full_unstemmed Low-Temperature Behaviour of Social and Economic Networks
title_sort low-temperature behaviour of social and economic networks
publisher MDPI AG
series Entropy
issn 1099-4300
publishDate 2013-08-01
description Real-world social and economic networks typically display a number of particular topological properties, such as a giant connected component, a broad degree distribution, the small-world property and the presence of communities of densely interconnected nodes. Several models, including ensembles of networks, also known in social science as Exponential Random Graphs, have been proposed with the aim of reproducing each of these properties in isolation. Here, we define a generalized ensemble of graphs by introducing the concept of graph temperature, controlling the degree of topological optimization of a network. We consider the temperature-dependent version of both existing and novel models and show that all the aforementioned topological properties can be simultaneously understood as the natural outcomes of an optimized, low-temperature topology. We also show that seemingly different graph models, as well as techniques used to extract information from real networks are all found to be particular low-temperature cases of the same generalized formalism. One such technique allows us to extend our approach to real weighted networks. Our results suggest that a low graph temperature might be a ubiquitous property of real socio-economic networks, placing conditions on the diffusion of information across these systems.
topic complex networks
graph ensembles
graph temperature
url http://www.mdpi.com/1099-4300/15/8/3148
work_keys_str_mv AT guidocaldarelli lowtemperaturebehaviourofsocialandeconomicnetworks
AT diegogarlaschelli lowtemperaturebehaviourofsocialandeconomicnetworks
AT thomasmafink lowtemperaturebehaviourofsocialandeconomicnetworks
AT sebastianeahnert lowtemperaturebehaviourofsocialandeconomicnetworks
_version_ 1725382048371179520