@inproceedings{8b56045f71454061b0f25773ab409497,
title = "Enhancing the Detection of Criminal Organizations in Mexico using ML and NLP",
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.",
keywords = "event data, information extraction, machine learning, maps, text classification",
author = "Javier Osorio and Alejandro Beltran",
note = "Funding Information: This research was possible thanks to the generous support of the Technology and Research Initiative Fund of the University of Arizona, and earlier grants from the National Science Foundation [SES-1123572], the Harry Frank Guggenheim Foundation, and the Drug Security and Democracy Fellowship of the Social Science Research Council – Open Society Foundations. Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 International Joint Conference on Neural Networks, IJCNN 2020 ; Conference date: 19-07-2020 Through 24-07-2020",
year = "2020",
month = jul,
doi = "10.1109/IJCNN48605.2020.9207039",
language = "English (US)",
series = "Proceedings of the International Joint Conference on Neural Networks",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2020 International Joint Conference on Neural Networks, IJCNN 2020 - Proceedings",
}