TY  - CHAP
N1  - Proceeedings of the Third International Workshop (WAW 2004) Rome, Italy, October 16, 2004. 
ID  - eprints1113
EP  - 187
T2  - Algorithms and Models for the Web-Graph
TI  - Communities Detection in Large Networks
AV  - none
UR  - http://dx.doi.org/10.1007/978-3-540-30216-2_15
SN  - 0302-9743
N2  - 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. 
ED  - Leonardi, Stefano
Y1  - 2004/10//
A1  - Capocci, Andrea
A1  - Servedio, Vito D. P.
A1  - Caldarelli, Guido
A1  - Colaiori, Francesca
PB  - Springer-Verlag
SP  - 181
T3  - Lecture Notes in Computer Science
ER  -