This thesis is about social and spatial network effects of organised crime. I propose an analysis of the internal structure of the Sicilian Mafia, applying spatial network analysis to an original dataset on a network of Cosa Nostra members. The aim is to clarify the structure of Mafia-type organizations, where spatial network analysis highlights novel aspects on how such a criminal group manages to pervade a geographical area. Therefore, in the first part the related literature is going to be analysed and it will be followed by a social network analysis of a Mafia related trial. In the last part, spatial effects will be studied. This study focuses on network and spatial implications in a criminal organisation such as Cosa Nostra which is something that was never tried before on organised crime groups. I have built a dataset from judicial source documents about the Mafia. I have worked on a specific act of the process obtained from a real investigation and I propose a strategy in order to identify nodes and links. This is prodromal to the social and spatial network analysis that follows. The main problem dealing with criminal investigations is that there is no complete nor reliable information. I suggest a system based on source selection and data organisation that allows me to diminish the impact of missing data. Once the dataset is created, it is analysed with social network tools in order to show similarities with other criminal groups. Then, each node is attached to its geographical coordinates and the network is analyzed on a map with spatial tools. Geolocalization of nodes and links allows us to assess a strong correlation between behavioural patterns and geography. This will be done in detail for the peculiar topology of the town of Palermo. Proximity and transitivity among nodes explains why specific areas are more targeted by extortion or criminal-led activities. Previous work has proposed a SNA of organized crime or other criminal networks. However, none of the existing works have analyzed organised crime in a spatial network context, in particular focusing on Cosa Nostra. No previous work has highlighted the internal structure of a Mafia group along with the geographical pattern of connections across members belonging to different mandamenti, as it is done here.

Social and spatial network analysis of organised crime

MUSOTTO, ROBERTO
2017-07-04

Abstract

This thesis is about social and spatial network effects of organised crime. I propose an analysis of the internal structure of the Sicilian Mafia, applying spatial network analysis to an original dataset on a network of Cosa Nostra members. The aim is to clarify the structure of Mafia-type organizations, where spatial network analysis highlights novel aspects on how such a criminal group manages to pervade a geographical area. Therefore, in the first part the related literature is going to be analysed and it will be followed by a social network analysis of a Mafia related trial. In the last part, spatial effects will be studied. This study focuses on network and spatial implications in a criminal organisation such as Cosa Nostra which is something that was never tried before on organised crime groups. I have built a dataset from judicial source documents about the Mafia. I have worked on a specific act of the process obtained from a real investigation and I propose a strategy in order to identify nodes and links. This is prodromal to the social and spatial network analysis that follows. The main problem dealing with criminal investigations is that there is no complete nor reliable information. I suggest a system based on source selection and data organisation that allows me to diminish the impact of missing data. Once the dataset is created, it is analysed with social network tools in order to show similarities with other criminal groups. Then, each node is attached to its geographical coordinates and the network is analyzed on a map with spatial tools. Geolocalization of nodes and links allows us to assess a strong correlation between behavioural patterns and geography. This will be done in detail for the peculiar topology of the town of Palermo. Proximity and transitivity among nodes explains why specific areas are more targeted by extortion or criminal-led activities. Previous work has proposed a SNA of organized crime or other criminal networks. However, none of the existing works have analyzed organised crime in a spatial network context, in particular focusing on Cosa Nostra. No previous work has highlighted the internal structure of a Mafia group along with the geographical pattern of connections across members belonging to different mandamenti, as it is done here.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11570/3110930
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