Uncovering the Structure of Criminal Organizations by Community Analysis: The Infinito Network

Criminal organizations tend to be clustered to reduce risks of detection and information leaks. Yet, the literature has so far neglected to explore the relevance of subgroups for their internal structure. The paper focuses on a case study drawing from a large law enforcement operation ("Operazione Infinito"). It applies methods of community analysis to explore the structure of a 'Ndrangheta (a mafia from Calabria, a southern Italian region) network representing the individuals' co-participation in meetings. The results show that the network is significantly clustered and that communities are partially associated with the internal organization of the 'Ndrangheta into different "locali" (similar to mafia families). The implications of these findings on the interpretation of the structure and functioning of the criminal network are discussed.

[1]  Satoru Kawai,et al.  An Algorithm for Drawing General Undirected Graphs , 1989, Inf. Process. Lett..

[2]  Claudio Castellano,et al.  Defining and identifying communities in networks. , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[3]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[4]  Alessandro Vespignani,et al.  Dynamical Processes on Complex Networks , 2008 .

[5]  Gisela Bichler,et al.  Networks of Collaborating Criminals: Assessing the Structural Vulnerability of Drug Markets , 2011 .

[6]  Simon A. Levin,et al.  Evolution of a modular software network , 2011, Proceedings of the National Academy of Sciences.

[7]  M. Meilă Comparing clusterings---an information based distance , 2007 .

[8]  Mark Newman,et al.  Networks: An Introduction , 2010 .

[9]  Vladimir Batagelj,et al.  Pajek - Analysis and Visualization of Large Networks , 2004, Graph Drawing Software.

[10]  Letizia Paoli,et al.  Mafia and organised crime in Italy: The unacknowledged successes of law enforcement , 2007 .

[11]  C. Lee Giles,et al.  Self-Organization and Identification of Web Communities , 2002, Computer.

[12]  Carlo Piccardi,et al.  Finding and Testing Network Communities by Lumped Markov Chains , 2011, PloS one.

[13]  Francesco Calderoni,et al.  Identifying Mafia Bosses from Meeting Attendance , 2014 .

[14]  Paul A. Bates,et al.  Cluster analysis of networks generated through homology: automatic identification of important protein communities involved in cancer metastasis , 2006, BMC Bioinformatics.

[15]  Federico Varese,et al.  How Mafias Migrate: The Case of the 'Ndrangheta' in Northern Italy , 2006 .

[16]  Shilpa Chakravartula,et al.  Complex Networks: Structure and Dynamics , 2014 .

[17]  Sergio Gómez,et al.  Size reduction of complex networks preserving modularity , 2007, ArXiv.

[18]  A. Arenas,et al.  Community analysis in social networks , 2004 .

[19]  Santo Fortunato,et al.  Community detection in graphs , 2009, ArXiv.

[20]  Fabio Della Rossa,et al.  Profiling core-periphery network structure by random walkers , 2013, Scientific Reports.

[21]  Carlo Morselli,et al.  The Efficiency/Security Trade-Off in Criminal Networks , 2007, Soc. Networks.

[22]  Erik M Bollt,et al.  Local method for detecting communities. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[23]  D. Mason,et al.  Compartments revealed in food-web structure , 2003, Nature.

[24]  Carlo Piccardi,et al.  Communities in Italian corporate networks , 2010 .

[25]  Jean-Loup Guillaume,et al.  Fast unfolding of communities in large networks , 2008, 0803.0476.

[26]  A. Clauset Finding local community structure in networks. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[27]  L. Paoli Mafia Brotherhoods: Organized Crime, Italian Style , 2003 .

[28]  M E J Newman,et al.  Modularity and community structure in networks. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[29]  Carlo Piccardi,et al.  Community analysis in directed networks: in-, out-, and pseudocommunities. , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.