%P 181-187
%T Communities Detection in Large Networks
%I Springer-Verlag
%O Proceeedings of the Third International Workshop (WAW 2004) Rome, Italy, October 16, 2004. 
%L eprints1113
%D 2004
%E Stefano Leonardi
%X We develop an algorithm to detect community structure in complex networks. The algorithm is based on spectral methods and takes into account weights and links orientations. Since the method detects efficiently clustered nodes in large networks even when these are not sharply partitioned, it turns to be specially suitable to 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. 
%A Andrea Capocci
%A Vito D. P. Servedio
%A Guido Caldarelli
%A Francesca Colaiori
%S Lecture Notes in Computer Science
%N 3243
%R 10.1007/978-3-540-30216-2_15
%B Algorithms and Models for the Web-Graph