Evidence map›Paper›PMID 39621604›Full record

ArticlePloS one2024

The Steiner tree Prosecutor: Revealing and disrupting criminal networks through a single suspect.

Fredy Troncoso, Richard Weber

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Fredy TroncosoDepartamento de Ingeniería Industrial, Facultad de Ingeniería, Universidad del Bío-Bío, Concepción, Chile.ORCID 0000-0002-9972-3123
Richard WeberDepartamento de Ingeniería Industrial, FCFM, Universidad de Chile, Santiago, Chile.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Disrupting a criminal organization requires a significant deployment of human resources, time, information, and financial investment. In the early stages of an investigation, details about a specific crime are typically scarce, often with no known suspect. The literature has shown that an effective approach for analyzing criminal organizations is social network analysis. This approach allows the use of traditional social network tools for analyzing criminal networks, as well as more sophisticated and recent tools. This article introduces a model called StPro, which enables the identification of members of a criminal organization starting from a single suspect. It utilizes linear optimization modeling based on Steiner trees. A suspect is used as the root node, and the resulting tree reveals a probable configuration of the criminal organization to which the suspect may belong. Its application to a real-world case demonstrates that there are no significant differences in effectiveness between the proposed model and the state-of-the-art in the literature, despite requiring less information. It also demonstrates how its application aided in the identification of a gang dedicated to violent crimes in Chile. These results highlight the strong capability of the proposed model to support criminal investigations.

Indexed as

CrimeAlgorithmsChileCriminalsHumansModels, TheoreticalSocial Network Analysis

Identifiers

PMID39621604
PMCPMC11611083

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.