Detecting communities in large networks

A. Capocci, V.D.P. Servedio, G. Caldarelli and F. Colaiori

Physica A: Statistical Mechanics and its Applications, 2005, vol. 352, issue 2, 669-676

Abstract: We develop an algorithm to detect community structure in complex networks. The algorithm is based on spectral methods and takes into account weights and link orientation. Since the method detects efficiently clustered nodes in large networks even when these are not sharply partitioned, it turns to be specially suitable for the analysis of social and information networks. We test the algorithm on a large-scale data-set from a psychological experiment of word association. In this case, it proves to be successful both in clustering words, and in uncovering mental association patterns.

Keywords: Networks and genealogical trees; Systems obeying scaling laws; Structures and organization in complex systems (search for similar items in EconPapers)
Date: 2005
References: View complete reference list from CitEc
Citations: View citations in EconPapers (20)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:352:y:2005:i:2:p:669-676

DOI: 10.1016/j.physa.2004.12.050

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