Titre
An Energy-Based Model for Spatial Social Networks
Type
article de conférence/colloque
Institution
UNIL/CHUV/Unisanté + institutions partenaires
Auteur(s)
A. Antonioni,
Auteure/Auteur
M. Egloff,
Auteure/Auteur
M. Tomassini,
Auteure/Auteur
Liens vers les personnes
Liens vers les unités
Titre du livre ou conférence/colloque
Advances in Artificial Life, ECAL 2013
Statut éditorial
Publié
Date de publication
2013-09
Première page
226
Dernière page/numéro d’article
231
Peer-reviewed
Oui
Résumé
In the past decade, thanks to abundant data and adequate soft- ware tools, complex networks have been thoroughly investi- gated in many disciplines. Most of this work has dealt with networks in which distances do not have physical meaning and are just dimensionless quantities measured in terms of edge hops. However, in many cases the physical space in which networks are embedded and the actual distances be- tween nodes are important, such as in geographical and trans- portation networks. The Random Geometric Graph (RGG) is a standard spatial network model that plays a role for spatial networks similar to the one played by the Erdo ̈s-Re ́nyi ran- dom graph for relational ones. In this work we present an extension of the RGG construction to define a new model to build bi-dimensional spatial networks based on energy as re- alistic constraint to create the links. The constructed networks have several properties in common with those of actual social networks.
PID Serval
serval:BIB_A35B693E455C
Date de création
2013-06-19T12:51:26.405Z
Date de création dans IRIS
2025-05-21T00:38:53Z