A transdisciplinary approach for generating synthetic but realistic domestic sex trafficking networks

Daniel, Kosmas,; Melander, Christina; Singerhouse, Emily; Sharkey, Thomas C.; Maass, Kayse Lee; Barrick, Kelle; Martin, Lauren

doi:10.1080/24725854.2023.2169418

Cited by 3 publications

(4 citation statements)

References 44 publications

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“…For example, “Mom & Pop” and “Crime Ring” networks may tend to operate with less attention to formalizing network structures that separate the traffickers from the victims since the number of traffickers is small. This is similar to the analytics discussed in Kosmas et al (2023a). The more sophisticated organizations may separate roles of traffickers more, with some traffickers having very little interactions with victims.…”

Section: Resultssupporting

confidence: 65%

“…Clark et al (forthcoming) modelled the actual revenues generated when traffickers force victims into different criminal markets and the fact that decisions will be made by the trafficker to maximize profits. Kosmas et al (2023a, 2023b) assumed that the goal of the trafficker is to maximize the number of controlled victims (subject to capacity constraints), which can indirectly model the revenues received by the trafficker. Xie and Aros-Vera (2022) did something similar in terms of victims flowing through a network in order to meet demand, which indirectly captures control.…”

Section: Resultsmentioning

confidence: 99%

“…This is a situation where decisions need to be made by the trafficker in order to operate the network and the model captures that their goal is to minimize the chances the operations are detected. Alternatively, others, such as Kosmas et al (2023aKosmas et al ( , 2023b have indirectly captured risks of trafficking by limiting the number of victims that the trafficker wishes to control. To date, risks identified in the literature focus on those that come from outside of the commercial sex market (e.g., law enforcement).…”

Section: Risksmentioning

confidence: 99%

See 2 more Smart Citations

Expanding Our Understanding of Traffickers and Their Operations: A Review of the Literature and Path Forward

Barrick,

Sharkey,

Maass

et al. 2023

Trauma, Violence, & Abuse

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Human trafficking is a serious crime and violation of human rights that results in numerous harms. Although the phenomenon is not new, scholarship on the issue has grown substantially since the first legal framework was passed in 2000. However, the existing literature has been criticized for its skewed focus on victims, among other things. The dearth of information on traffickers and their operations limits our ability to reduce or prevent perpetration. The current study presents a comprehensive and critical review of the existing literature focused on traffickers to synthesize what is already known and highlight the key gaps. Twenty-nine articles met the inclusion criteria of (1) focusing on traffickers and their operations and (2) relying on data either directly from traffickers or sources that contained detailed information about criminal cases against traffickers. We used an iterative process to identify relevant studies, which included collecting articles of which we were already familiar or were identified in existing reviews, searching their reference lists, and conducting cited-by searches until saturation was reached. Topics found in the extant literature included: characteristics of traffickers, relationships between traffickers and victims, organizational characteristics and networks, operations, connections with other crimes, motivations, perceptions of behavior, and risks associated with trafficking. It concludes with recommendations for future research and a discussion of how bridging gaps in the literature could support more rigorous mathematical modeling that is needed to identify and assess promising perpetration prevention and intervention strategies.

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Section: Resultssupporting

confidence: 65%

Section: Resultsmentioning

confidence: 99%

Section: Risksmentioning

confidence: 99%

See 1 more Smart Citation

Expanding Our Understanding of Traffickers and Their Operations: A Review of the Literature and Path Forward

Barrick,

Sharkey,

Maass

et al. 2023

Trauma, Violence, & Abuse

Self Cite

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“…This approach could lead to more resilient and adaptive network designs, thereby enhancing decision-making processes in areas such as infrastructure planning, supply chain and logistics. Additionally, considering the fact that for many networks we do not have a full picture of all the existing nodes and edges (see, e.g., illicit networks which have attracted significant recent interest as in the works by Kosmas et al (2023); Anzoom et al ( 2023)), stochastic extensions to group centrality can lead to more realistic identification of key actors in networks with hidden elements.…”

Section: Future Workmentioning

confidence: 99%

The Star Degree Centrality Problem: A Decomposition Approach

Camur

Sharkey

Vogiatzis

2022

INFORMS Journal on Computing

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We consider the problem of identifying the induced star with the largest cardinality open neighborhood in a graph. This problem, also known as the star degree centrality (SDC) problem, is shown to be [Formula: see text]-complete. In this work, we first propose a new integer programming (IP) formulation, which has a smaller number of constraints and nonzero coefficients in them than the existing formulation in the literature. We present classes of networks in which the problem is solvable in polynomial time and offer a new proof of [Formula: see text]-completeness that shows the problem remains [Formula: see text]-complete for both bipartite and split graphs. In addition, we propose a decomposition framework that is suitable for both the existing and our formulations. We implement several acceleration techniques in this framework, motivated by techniques used in Benders decomposition. We test our approaches on networks generated based on the Barabási–Albert, Erdös–Rényi, and Watts–Strogatz models. Our decomposition approach outperforms solving the IP formulations in most of the instances in terms of both solution time and quality; this is especially true for larger and denser graphs. We then test the decomposition algorithm on large-scale protein–protein interaction networks, for which SDC is shown to be an important centrality metric. Summary of Contribution: In this study, we first introduce a new integer programming (NIP) formulation for the star degree centrality (SDC) problem in which the goal is to identify the induced star with the largest open neighborhood. We then show that, although the SDC can be efficiently solved in tree graphs, it remains [Formula: see text]-complete in both split and bipartite graphs via a reduction performed from the set cover problem. In addition, we implement a decomposition algorithm motivated by Benders decomposition together with several acceleration techniques to both the NIP formulation and the existing formulation in the literature. Our experimental results indicate that the decomposition implementation on the NIP is the best solution method in terms of both solution time and quality.

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Modeling Disruptions to Sex Trafficking Networks with Other Forced Illegal Activities

Clark,

Sharkey,

Ayler

et al. 2023

Journal of Human Trafficking

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A transdisciplinary approach for generating synthetic but realistic domestic sex trafficking networks

Cited by 3 publications

References 44 publications

Expanding Our Understanding of Traffickers and Their Operations: A Review of the Literature and Path Forward

Expanding Our Understanding of Traffickers and Their Operations: A Review of the Literature and Path Forward

The Star Degree Centrality Problem: A Decomposition Approach

Modeling Disruptions to Sex Trafficking Networks with Other Forced Illegal Activities

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