Social network analysis: the use of graph distances to compare artificial and criminal networks

Ficara, Annamaria; Curreri, Francesco; Cavallaro, Lucia; Meo, Pasquale De; Fiumara, Giacomo; Bagdasar, Ovidiu; Liotta, Antonio

doi:10.20517/jsegc.2021.08

Cited by 2 publications

(6 citation statements)

References 38 publications

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“…In one of our previous work [4], we used some popular network models like random networks (i.e. the ER [36] model), small-world networks (i.e.…”

Section: Resultsmentioning

confidence: 99%

“…Our analysis focuses on two real criminal networks related to a specific anti-mafia operation called Montagna [4]- [6], [8]- [10].…”

Section: Criminal Network Datasetmentioning

confidence: 99%

“…Herein, we borrow methods and tools from Social Network Analysis (SNA) to investigate the effectiveness of several law enforcement interventions against two Mafia networks, based on a real-world dataset built from a major anti-mafia operation called "Montagna" which was concluded in 2007. This dataset was used in different studies on Mafia networks through SNA to analyze the structure of such networks [3], [4], identify subgroups and highlight actors in strategic positions [5]- [7], and develop disruption and prevention methods [8]- [10].…”

Section: Introductionmentioning

confidence: 99%

“…Then, we want to verify if it is possible to create a network model for criminal network disruption using an artificial network with the same characteristics of a Mafia network. In our previous work [4], we used some popular network models like the Erdös-Rényi (ER) [36] model, the Watts-Strogatz (WS) [37] model and different configurations of the Barabási-Albert (BA) [38] model to replicate the topology of a criminal network. Our experiments identified the BA model as the one which better represents a criminal network.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Human and Social Capital Strategies for Mafia Network Disruption

Ficara

Curreri

Fiumara

et al. 2023

IEEE Trans.Inform.Forensic Secur.

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Social Network Analysis (SNA) is an interdisciplinary science that focuses on discovering the patterns of individuals interactions. In particular, practitioners have used SNA to describe and analyze criminal networks to highlight subgroups, key actors, strengths and weaknesses in order to generate disruption interventions and crime prevention systems. In this paper, the effectiveness of a total of seven disruption strategies for two real Mafia networks is investigated adopting SNA tools. Three interventions targeting actors with a high level of social capital and three interventions targeting those with a high human capital are put to the test and compared between each other and with random node removal. Similar tests on artificial model networks have also been carried out. Simulations show that actor removal based on social capital proves to be the most effective strategy, by leading to the total disruption of the criminal network in the least number of steps. The removal of a specific figure of a Mafia family such as the Caporegime seems also promising in the network disruption.

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“…In one of our previous work [4], we used some popular network models like random networks (i.e. the ER [36] model), small-world networks (i.e.…”

Section: Resultsmentioning

confidence: 99%

“…Our analysis focuses on two real criminal networks related to a specific anti-mafia operation called Montagna [4]- [6], [8]- [10].…”

Section: Criminal Network Datasetmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Human and Social Capital Strategies for Mafia Network Disruption

Ficara

Curreri

Fiumara

et al. 2023

IEEE Trans.Inform.Forensic Secur.

Self Cite

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show abstract

“…In the field of criminal network analysis, SNA is exploited to systematically examine criminal networks in order to attain greater insights about criminal behavior [20][21][22]. SNA allows graphically visualizing complex social structures and examining them systematically by computing the relational patterns of nodes (which can represent the actors involved) and connections (which represent a kind of tie between them).…”

Section: Introductionmentioning

confidence: 99%

Covert Network Construction, Disruption, and Resilience: A Survey

et al. 2022

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Covert networks refer to criminal organizations that operate outside the boundaries of the law; they can be mainly classified as terrorist networks and criminal networks. We consider how Social Network Analysis (SNA) is used to analyze such networks in order to attain a greater knowledge of criminal behavior. In fact, SNA allows examining the network structure and functioning by computing relevant metrics and parameters to identify roles, positions, features, and other network functioning that are not otherwise easily discovered at first glance. This is why Law Enforcement Agencies (LEAs) are showing growing interest in SNA, which is also used to identify weak spots and disrupt criminal groups. This paper provides a literature review and a classification of methods and real-case applications of disruption techniques. It considers covert network adaptability to such dismantling attempts, herein referred to as resilience. Critical problems of SNA in criminal studies are discussed, including data collection techniques and the inevitable incompleteness and biases of real-world datasets, with the aim of promoting a new research stream for both dismantling techniques and data collection issues.

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Social network analysis: the use of graph distances to compare artificial and criminal networks

Cited by 2 publications

References 38 publications

Human and Social Capital Strategies for Mafia Network Disruption

Human and Social Capital Strategies for Mafia Network Disruption

Covert Network Construction, Disruption, and Resilience: A Survey

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