Enhancing the Detection of Criminal Organizations in Mexico using ML and NLP

Javier Osorio, Alejandro Beltran

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper relies on Machine Learning (ML) and supervised Natural Language Processing (NLP) to generate a geo-referenced database on the violent presence of Mexican Criminal Organizations (MCOs) between 2000-2018. This application responds to the need for high-quality data on criminal groups to inform academic and policy analysis in a context of intense violence such as Mexico. Powered by ML and NLP tools, this computational social science application processes a vast collection of news stories written in Spanish to track MCOs' violent presence. The unprecedented granularity of the data allows disaggregating daily-municipal information for 10 main MCOs comprising more than 200 specific criminal cells.

Original languageEnglish (US)
Title of host publication2020 International Joint Conference on Neural Networks, IJCNN 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728169262
DOIs
StatePublished - Jul 2020
Event2020 International Joint Conference on Neural Networks, IJCNN 2020 - Virtual, Glasgow, United Kingdom
Duration: Jul 19 2020Jul 24 2020

Publication series

NameProceedings of the International Joint Conference on Neural Networks

Conference

Conference2020 International Joint Conference on Neural Networks, IJCNN 2020
Country/TerritoryUnited Kingdom
CityVirtual, Glasgow
Period7/19/207/24/20

Keywords

  • event data
  • information extraction
  • machine learning
  • maps
  • text classification

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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