Characterizing Crimes from Web / Caracterizando Crimes da Web

Authors

  • Márcio Vinícius Campos da Silveira
  • Wladmir Cardoso Brandão

DOI:

https://doi.org/10.34117/bjdv5n11-290

Keywords:

crime analytics, crime characterization, pattern recognition, clustering analysis.

Abstract

Crime prevention requires an effective use of police resources, which demands the access of criminal information for planning security actions. The number of crime occurrences is higher than the officially reported numbers. Many victims do not report crimes directly to the security agencies. Instead, they prefer to anonymously report using different channels, such as the Web. In this article, we introduce our approach to characterize crimes reported in the Web. Particularly, we collect criminal data from popular websites that store crime occurrences, and we use clustering analysis to discover crime patterns on the collected data. Applying our approach to a popular Brazilian crime report website, we observe that more than 41% of the crimes were not reported to the security agencies, and most of them are thefts and robberies occurring at night and dawn. In addition, minor offenses present different patterns of serious crimes. Moreover, crime patterns are different in rich and poor neighborhood.

 

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Published

2019-11-26

How to Cite

Silveira, M. V. C. da, & Brandão, W. C. (2019). Characterizing Crimes from Web / Caracterizando Crimes da Web. Brazilian Journal of Development, 5(11), 26608–26619. https://doi.org/10.34117/bjdv5n11-290

Issue

Section

Original Papers