ArticlePloS one2016
Link Prediction in Criminal Networks: A Tool for Criminal Intelligence Analysis.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Explainable multi-agent learning for adaptive terrorist network disruption.Scientific reports · 2026Article
- Marrying for power: Gendered alliances in mafias.PloS one · 2026Article
- Link prediction of heterogeneous complex networks based on an improved embedding learning algorithm.PloS one · 2025Article
- CompLex: Legal systems through the lens of complexity science.Europhysics letters · 2025Article
- A Survey on Hyperlink Prediction.IEEE transactions on neural networks and learning systems · 2024Article
- Triadic influence as a proxy for compatibility in social relationships.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Reconstructing Sparse Multiplex Networks with Application to Covert Networks.Entropy (Basel, Switzerland) · 2023Article
- Characterization of Group Behavior of Corruption in Construction Projects Based on Contagion Mechanism.Computational intelligence and neuroscience · 2022Article
- Progresses and challenges in link prediction.iScience · 2021Review
- Article
- Link Prediction through Deep Generative Model.iScience · 2020Article
- Analyzing the Bills-Voting Dynamics and Predicting Corruption-Convictions Among Brazilian Congressmen Through Temporal Networks.Scientific reports · 2019Article
- A unified framework for link prediction based on non-negative matrix factorization with coupling multivariate information.PloS one · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The problem of link prediction has recently received increasing attention from scholars in network science. In social network analysis, one of its aims is to recover missing links, namely connections among actors which are likely to exist but have not been reported because data are incomplete or subject to various types of uncertainty. In the field of criminal investigations, problems of incomplete information are encountered almost by definition, given the obvious anti-detection strategies set up by criminals and the limited investigative resources. In this paper, we work on a specific dataset obtained from a real investigation, and we propose a strategy to identify missing links in a criminal network on the basis of the topological analysis of the links classified as marginal, i.e. removed during the investigation procedure. The main assumption is that missing links should have opposite features with respect to marginal ones. Measures of node similarity turn out to provide the best characterization in this sense. The inspection of the judicial source documents confirms that the predicted links, in most instances, do relate actors with large likelihood of co-participation in illicit activities.
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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.