2007/10/09 by Filipi Nascimento Silva, Marilza A. Rodrigues, Marilza A. Rodrigues Tognetti +2
Computer Science · Engineering · Mathematics · Physics and Astronomy · #Artificial intelligence #Cartography #Cluster analysis #Clustering coefficient #Combinatorics #Community structure #Complex Network Analysis Techniques #Complex network #Computer science #Concentric #Convergence (economics) #Data mining #Engineering #Geography #Hierarchical clustering #Hierarchical network model #Mathematics #Node (physics) #Opinion Dynamics and Social Influence #Peer-to-Peer Network Technologies #Scale (ratio) #Scale-free network #Set (abstract data type) #Statistics #Topology (electrical circuits) #World Wide Web #physics.data-an #physics.soc-ph
paper · pdf · doi:10.1016/j.physa.2008.06.034
15 pages, 13 figures
arxiv created 2007/10/09 · openalex publication_date 2008/07/03 · arxiv updated 2012/03/22 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05
Differently from theoretical scale-free networks, most of real networks present multi-scale behavior with nodes structured in different types of functional groups and communities. While the majority of approaches for classification of nodes in a complex network has relied on local measurements of the topology/connectivity around each node, valuable information about node functionality can be obtained by Concentric (or Hierarchical) Measurements. In this paper we explore the possibility of using a set of Concentric Measurements and agglomerative clustering methods in order to obtain a set of functional groups of nodes. Concentric clustering coefficient and convergence ratio are chosen as segregation parameters for the analysis of a institutional collaboration network including various known communities (departments of the University of São Paulo). A dendogram is obtained and the results are analyzed and discussed. Among the interesting obtained findings, we emphasize the scale-free nature of the obtained network, as well as the identification of different patterns of authorship emerging from different areas (e.g. human and exact sciences). Another interesting result concerns the relatively uniform distribution of hubs along the concentric levels, contrariwise to the non-uniform pattern found in theoretical scale free networks such as the BA model.