A Machine Learning Framework for Ranking Cities Considering Crimes Against Women: A Case Study in Northeast Brazil
Resumo
Violence against women is a profound infringement of human rights and stands as one of the most severe public health issues globally. It is comprehensively defined as any act of physical, sexual, psychological, or property-based violence perpetrated against a woman, constituting behaviour that transgresses women's dignity, rights, and freedom. In this context, this study introduces a machine learning model aimed at classifying cities based on the potential prevalence of violence against women. The model is trained utilizing a comprehensive city database, generating classifications of cities into three levels: low, medium, and high violence. The chosen algorithm, ExtraTrees, demonstrated a noteworthy accuracy rate of 90%.Referências
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Brasil. Constituição da República Federativa do Brasil de 1988. Available in: [link]. Access in: Feb. 23, 2021.
Bowen, D.A., Mercer Kollar, L.M., Wu, D.T., Fraser, D.A., Flood, C.E., Moore, J.C., Mays, E.W. & Sumner, S.A. Ability of crime, demographic and business data to forecast areas of increased violence. International Journal of Injury Control and Safety Promotion, v.25, n.4, p.443-448, 2018.
De Lima, F., & Marinho, E. (2017). Public security in Brazil: Efficiency and technological gaps. EconomiA, 18 (1), 129-145.
Li, Y-S. & Qi, M-L. An approach for understanding offender modus operandi to detect serial robbery crimes. Journal of Computational Science, v.36, 2019.
Lima, E., Vieira, T. & Costa, E.B. Evaluating deep models for absenteeism prediction of public security agents. Applied Soft Computing Journal, v.91, 2020.
Ministério Público. Tipos de violência. Disponível em: [link]. Acesso em: 20 de jul. 2022.
Mohri, M., Rostamizadeh, A. & Talwalkar, A. Foundations of Machine Learning, MIT Press, 2018.
Nova D., Ferreira A. & Cortez P. A Machine Learning Approach to Detect Violent Behaviour from Video, 2019. In: Cortez P., Magalhães L., Branco P., Portela C., Adão T. (eds) Intelligent Technologies for Interactive Entertainment. INTETAIN 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, v. 273. Springer
ToppiReddy, H.K.R., Saini, B. & Mahajan, G. Crime Prediction & Monitoring Framework Based on Spatial Analysis. In: Procedia Computer Science, v.132, p.696-705, 2018.
Turet, J., Costa, A.P.C.S., Hybrid methodology for analysis of structured and unstructured data to support decision-making in public security, Data & Knowledge Engineering, Volume 141, 2022, 102056, ISSN 0169-023X. DOI: 10.1016/j.datak.2022.102056.
Publicado
20/07/2025
Como Citar
TURET, Jean; NEPOMUCENO, Thyago.
A Machine Learning Framework for Ranking Cities Considering Crimes Against Women: A Case Study in Northeast Brazil. In: WORKSHOP SOBRE AS IMPLICAÇÕES DA COMPUTAÇÃO NA SOCIEDADE (WICS), 6. , 2025, Maceió/AL.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 189-197.
ISSN 2763-8707.
DOI: https://doi.org/10.5753/wics.2025.7930.
