Table of Contents
Journal of Complex Systems
Volume 2014, Article ID 354385, 10 pages
http://dx.doi.org/10.1155/2014/354385
Research Article

Group Measures and Modeling for Social Networks

1CESI, 959 Rue de la Bergeresse, 45160 Olivet, France
2LIFO, University of Orléans, 45067 Orléans, France

Received 20 May 2014; Revised 27 August 2014; Accepted 29 August 2014; Published 30 September 2014

Academic Editor: Juan Luis Cabrera

Copyright © 2014 Vincent Levorato. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Social network modeling is generally based on graph theory, which allows for study of dynamics and emerging phenomena. However, in terms of neighborhood, the graphs are not necessarily adapted to represent complex interactions, and the neighborhood of a group of vertices can be inferred from the neighborhoods of each vertex composing that group. In our study, we consider that a group has to be considered as a complex system where emerging phenomena can appear. In this paper, a formalism is proposed to resolve this problematic by modeling groups in social networks using pretopology as a generalization of the graph theory. After giving some definitions and examples of modeling, we show how some measures used in social network analysis (degree, betweenness, and closeness) can be also generalized to consider a group as a whole entity.