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An urban network percolation based spatiotemporal analysis of crime hotspot using directed acyclic graphs

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  • Perez, Yuri
  • Gonçalves, Luis Fernando
  • Pereira, Fabio Henrique

Abstract

This paper presents an exploration of crime data through the application of complex network methods. Our primary objective is to analyze spatiotemporal crime dynamics using a complex network model based on the percolation of directed acyclic graphs, introducing a dual criterion of spatial and temporal proximity. Leveraging a dataset comprising vehicle theft incidents from 2014 to 2023, sourced from the Department of Public Safety of São Paulo, our empirical investigation highlights a downward trend in criminal activity from 2014 to 2020, with a substantial increase in 2023. Notably, the geographical stability of crime clusters across different time scales emerges as a significant finding. We detected varying frequencies and spatial densities throughout the city, suggesting a complex, heterogeneous array of crime patterns. Our model offers a promising avenue for shaping policing strategies based on spatial density and temporal patterns.

Suggested Citation

  • Perez, Yuri & Gonçalves, Luis Fernando & Pereira, Fabio Henrique, 2025. "An urban network percolation based spatiotemporal analysis of crime hotspot using directed acyclic graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 669(C).
    • Handle: RePEc:eee:phsmap:v:669:y:2025:i:c:s0378437125001621
    DOI: 10.1016/j.physa.2025.130510
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    References listed on IDEAS

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    1. Perez, Yuri & Pereira, Fabio Henrique, 2023. "Estimating pandemic effects in urban mass transportation systems: An approach based on visibility graphs and network similarity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 620(C).
    2. Anthony Braga & Andrew Papachristos & David Hureau, 2012. "Hot spots policing effects on crime," Campbell Systematic Reviews, John Wiley & Sons, vol. 8(1), pages 1-96.
    3. Carlos Caminha & Vasco Furtado & Tarcisio H C Pequeno & Caio Ponte & Hygor P M Melo & Erneson A Oliveira & José S Andrade Jr., 2017. "Human mobility in large cities as a proxy for crime," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-13, February.
    4. Balmori de la Miyar, Jose Roberto & Hoehn-Velasco, Lauren & Silverio-Murillo, Adan, 2021. "Druglords don’t stay at home: COVID-19 pandemic and crime patterns in Mexico City," Journal of Criminal Justice, Elsevier, vol. 72(C).
    5. Dehdarian, Amin & Tucci, Christopher L, 2021. "A complex network approach for analyzing early evolution of smart grid innovations in Europe," Applied Energy, Elsevier, vol. 298(C).
    6. Rong, Qingnan & Zhang, Jun & Sun, Xiaoqian & Wandelt, Sebastian, 2022. "On the estimation of percolation thresholds for real networks," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    7. Quick, Matthew & Li, Guangquan & Brunton-Smith, Ian, 2018. "Crime-general and crime-specific spatial patterns: A multivariate spatial analysis of four crime types at the small-area scale," Journal of Criminal Justice, Elsevier, vol. 58(C), pages 22-32.
    8. Du, Ruijin & Li, Jingjing & Dong, Gaogao & Tian, Lixin & Qing, Ting & Fang, Guochang & Dong, Yujuan, 2020. "Percolation analysis of urban air quality: A case in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    9. Marcos Oliveira & Carmelo Bastos-Filho & Ronaldo Menezes, 2017. "The scaling of crime concentration in cities," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-13, August.
    10. Duccio Piovani & Carlos Molinero & Alan Wilson, 2017. "Urban retail location: Insights from percolation theory and spatial interaction modeling," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-13, October.
    11. Carter, Jeremy G. & Mohler, George & Raje, Rajeev & Chowdhury, Nahida & Pandey, Saurabh, 2021. "The Indianapolis harmspot policing experiment," Journal of Criminal Justice, Elsevier, vol. 74(C).
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