ORIGINAL RESEARCH article
Front. Big Data
Sec. Data Science
Volume 8 - 2025 | doi: 10.3389/fdata.2025.1648730
Structure and Dynamics Mapping of Illicit Firearms Trafficking Using Artificial Intelligence Models
Provisionally accepted- Orion Integrated Biosciences, Larchmont, United States
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Illicit firearms trafficking imposes severe social and economic costs, eroding public safety, distorting markets, and weakening state capacity while affecting vulnerable populations. Despite its profound consequences for global health, trade, and security, the network structure and dynamics of illicit firearms trafficking are one of the most elusive dimensions of transnational organized crime. News reports documenting these events are fragmented across countries, languages, and outlets with different levels of quality and bias. Motivated by the disproportionate impact in Latin America, this study operationalizes the International Classification of Crime for Statistical Purposes (ICCS) to convert multilingual news into structured and auditable indicators through a three-part analytic pipeline using BERT architecture and zero-shot prompts for entity resolution. This analytical approach generated outputs enriched with named entities, geocodes, and timestamps and stored as structured JSON, enabling reproducible analysis. The results of this implementation identified 8,171 firearms trafficking reports published from 2014 through July 2024. The number of firearms-related reports rose sharply over the decade. Incidents increase roughly tenfold, and the geographic footprint expands from about twenty to more than eighty countries, with a one hundred fifty five percent increase from 2022 to 2023. Correlation analysis links firearms trafficking to twelve other ICCS Level 1 categories, including drug trafficking, human trafficking, homicide, terrorism, and environmental crimes. Entity extraction and geocoding show a clear maritime bias; ports are referenced about six times more often than land or air routes. The analysis yielded eighty-five distinct points of entry or exit and forty-one named transnational criminal organizations, though attribution appears in only about forty percent of reports. This is the first automated and multilingual application of ICCS to firearms trafficking using modern language technologies. The outputs enable early warning through signals associated with ICCS categories, cross-border coordination focused on recurrent routes and high-risk ports, and evaluation of interventions. In short, embedding ICCS in a reproducible pipeline transforms fragmented media narratives into comparable evidence for strategic, tactical, and operational environments.
Keywords: firearms trafficking, ICCS, BERT, zero-shot prompts, Entity resolution, named entities, Geocodes, Timestamps
Received: 08 Jul 2025; Accepted: 01 Sep 2025.
Copyright: © 2025 Valdivia-Granda. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Willy A Valdivia-Granda, Orion Integrated Biosciences, Larchmont, United States
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