Group Measures and Modeling for Social Networks. (30th September 2014)

• Record Type: Journal Article
• Authors: Levorato, Vincent
• Other Names: Cabrera Juan Luis Academic Editor.
• Is Part Of: Journal of complex systems. Volume 2014(2014)
• Publication Date: 2014-09-30
• Subjects: System analysis -- Periodicals; Computational complexity -- Periodicals; Coupled problems (Complex systems) -- Periodicals; Systems engineering -- Periodicals; Computational complexity; Coupled problems (Complex systems); System analysis; Systems engineering; Electronic journals; Periodicals; 003
• DOI: 10.1155/2014/354385
• Languages: English
• ISSNs: 2356-7244

Abstract

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.