Universality of political corruption networks

Martins, Alvaro F.; Cunha, Bruno Requião da; Hanley, Quentin S.; Gonçalves, Sebastián; Perc, Matjaž; Ribeiro, Haroldo V.

doi:10.1038/s41598-022-10909-2

Cited by 10 publications

(10 citation statements)

References 35 publications

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“…These results indicate that the structure of corruption networks is more redundant than the one observed for the criminal intelligence network. Indeed, corruption networks are formed by a set of complete graphs representing people involved in political scandals that are in turn connected with each other by the recidivism of a small number of agents 14 . In contrast, criminal intelligence networks can have more complex connectivity patterns that are uncovered by police investigations 15 .…”

Section: Resultsmentioning

confidence: 99%

“…13 and the Spanish data were obtained from Ref. 14 . In both networks, nodes represent people involved in political scandals and connections among them indicate individuals engaged at least once in the same corruption case.…”

Section: Datasetsmentioning

confidence: 99%

“…Datasets describing the corruption networks and the police intelligence network are freely available on the internet (see Refs. [13][14][15] ). The dataset for the criminal financial network is available from the corresponding authors upon request.…”

Section: Data Availabilitymentioning

confidence: 99%

“…In line with other research on social systems [7][8][9][10][11] , complex networks can suitably describe the intricate relations among criminals and reveal the patterns based on which criminal organizations operate. Beyond theoretical explorations, recent articles have empirically demonstrated that these methods can be useful in investigations involving drug trafficking 12 , political networks 13,14 , police intelligence networks 15 , cartel detection 16 , money laundering 17 , pedophile rings 18 , and a range of other examples [19][20][21][22][23][24] .…”

Section: Introductionmentioning

confidence: 99%

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Machine learning partners in criminal networks

Lopes

Cunha

Martins

et al. 2022

Sci Rep

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Recent research has shown that criminal networks have complex organizational structures, but whether this can be used to predict static and dynamic properties of criminal networks remains little explored. Here, by combining graph representation learning and machine learning methods, we show that structural properties of political corruption, police intelligence, and money laundering networks can be used to recover missing criminal partnerships, distinguish among different types of criminal and legal associations, as well as predict the total amount of money exchanged among criminal agents, all with outstanding accuracy. We also show that our approach can anticipate future criminal associations during the dynamic growth of corruption networks with significant accuracy. Thus, similar to evidence found at crime scenes, we conclude that structural patterns of criminal networks carry crucial information about illegal activities, which allows machine learning methods to predict missing information and even anticipate future criminal behavior.

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Section: Resultsmentioning

confidence: 99%

Section: Datasetsmentioning

confidence: 99%

Section: Data Availabilitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Machine learning partners in criminal networks

Lopes

Cunha

Martins

et al. 2022

Sci Rep

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“…Many researchers have applied the infectious disease dynamics model to analyze violence, corruption, and other social situations. Of those researchers, some applied mathematical modeling analysis on the dynamics of university student animosity towards mathematics with optimal control theory [24], some applied modeling for the dynamics of racism in cyberspace [25], and some applied modeling for violence [26][27][28], some applied modeling for the stability analysis of corruption [29], and others study universality of political corruption networks [30]. But, to the best of our knowledge, no one has developed and analyzed a mathematical model of the di usion of violence.…”

Section: Introductionmentioning

confidence: 99%

Mathematical Model Analysis on the Diffusion of Violence

Terefe

2022

International Journal of Mathematics and Mathematical Sciences

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Recently, violence has been a very common and serious public health problem in the world. In this new mathematical modeling tactic study, we formulated and examined the firsthand violence mathematical model with five distinct classes of the human population (susceptible, violence-exposed, violence, negotiated, and reconciled). The model takes into account the diffusion of violence and infection. The violence-free and violence-dominance model equilibrium points are calculated, and their local and global stabilities are analyzed. The model threshold values are obtained. As a result of the model analysis, the violence diffusion is under control if the basic reproduction number is less than unity, and it diffuses through the community if this number exceeds unity. Besides, the sensitivity analysis of the parameter values of the basic reproduction number is demonstrated. We have applied the MATLAB ode45 solver to illustrate the numerical results of the model. Finally, from analytical and numerical solutions, we obtain jointly equivalent and consistent results.

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Organized crime behavior of shell-company networks in procurement: prevention insights for policy and reform

Nicolás-Carlock¹,

Luna-Pla²

2023

Trends Organ Crim

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In recent years, the analysis of economic crime and corruption in procurement has benefited from integrative studies that acknowledge the interconnected nature of the procurement ecosystem. Following this line of research, we present a networks approach for the analysis of shell-companies operations in procurement that makes use of contracting and ownership data under one framework to gain knowledge about the organized crime behavior that emerges in this setting. In this approach, ownership and management data are used to identify connected components in shell-company networks that, together with the contracting data, allows to develop an alternative representation of the traditional buyer-supplier network: the module-component bipartite network, where the modules are groups of buyers and the connected components are groups of suppliers. This is applied to two documented cases of procurement corruption in Mexico characterized by the involvement of large groups of shell-companies in the misappropriation of millions of dollars across many sectors. We quantify the economic impact of single versus connected shell-companies operations. In addition, we incorporate metrics for the diversity of operations and favoritism levels. This paper builds into the quantitative organized crime in the private sector studies and contributes by proposing a networks approach for preventing fraud and understanding the need for legal reforms.

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Universality of political corruption networks

Cited by 10 publications

References 35 publications

Machine learning partners in criminal networks

Machine learning partners in criminal networks

Mathematical Model Analysis on the Diffusion of Violence

Organized crime behavior of shell-company networks in procurement: prevention insights for policy and reform

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