Visualizing criminal networks reconstructed from mobile phone records

In the fight against the racketeering and terrorism, knowledge about the structure and the organization of criminal networks is of fundamental importance for both the investigations and the development of efficient strategies to prevent and restrain crimes. Intelligence agencies exploit information...

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Detalles Bibliográficos
Autor principal: Catanese, Salvatore (Autor)
Otros Autores: Fiumara, Giacomo ; Ferrara, Emilio ; De Meo, Pasquale
Tipo de documento: Electrónico Libro
Lenguaje:Inglés
Publicado: 2014
En:Año: 2014
Acceso en línea: Volltext (kostenfrei)
Verificar disponibilidad: HBZ Gateway
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245 1 0 |a Visualizing criminal networks reconstructed from mobile phone records 
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520 |a In the fight against the racketeering and terrorism, knowledge about the structure and the organization of criminal networks is of fundamental importance for both the investigations and the development of efficient strategies to prevent and restrain crimes. Intelligence agencies exploit information obtained from the analysis of large amounts of heterogeneous data deriving from various informative sources including the records of phone traffic, the social networks, surveillance data, interview data, experiential police data, and police intelligence files, to acquire knowledge about criminal networks and initiate accurate and destabilizing actions. In this context, visual representation techniques coordinate the exploration of the structure of the network together with the metrics of social network analysis. Nevertheless, the utility of visualization tools may become limited when the dimension and the complexity of the system under analysis grow beyond certain terms. In this paper we show how we employ some interactive visualization techniques to represent criminal and terrorist networks reconstructed from phone traffic data, namely foci, fisheye and geo-mapping network layouts. These methods allow the exploration of the network through animated transitions among visualization models and local enlargement techniques in order to improve the comprehension of interesting areas. By combining the features of the various visualization models it is possible to gain substantial enhancements with respect to classic visualization models, often unreadable in those cases of great complexity of the network.Comment: 6 pages, 4 figures, DataWiz 2014 (held in conjunction with ACM Hypertext 2014 
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