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<p>Urban environments have long been a central focus for crime researchers across diverse disciplines. Over the past&#xa0;few decades, this heterogeneous area of inquiry has experienced substantial methodological and empirical change, driven by the emergence of novel datasets and the increasing use of flexible computational methods. In this Review, we take stock of this evolution and examine the potential that these developments hold for advancing urban crime research, while also addressing the persistent challenges that continue to shape the field. Building on this overview, we emphasize the promise that computational methods offer for more rigorous causal inference beyond traditional prediction tasks. Finally, we outline three key directions for future research to ensure that new data and computational tools are used effectively: greater integration across disciplines, improved open science standards and a broader scope of inquiry beyond Western contexts. In doing so, we aim to support more rigorous research and inform the development of more effective policies for safer and more sustainable cities worldwide.</p>

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Computational approaches and the future of urban crime research

  • 期刊论文

  • 发表日期：

    2026年7月8日

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  • Gian Maria Campedelli,
  • Zubin Jelveh,
  • Aaron Chalfin,
  • Daniel Semenza,
  • Eric Piza,
  • Ariadna Albors Zumel,
  • Bruno Lepri,
  • Patrick Sharkey

摘要

Urban environments have long been a central focus for crime researchers across diverse disciplines. Over the past few decades, this heterogeneous area of inquiry has experienced substantial methodological and empirical change, driven by the emergence of novel datasets and the increasing use of flexible computational methods. In this Review, we take stock of this evolution and examine the potential that these developments hold for advancing urban crime research, while also addressing the persistent challenges that continue to shape the field. Building on this overview, we emphasize the promise that computational methods offer for more rigorous causal inference beyond traditional prediction tasks. Finally, we outline three key directions for future research to ensure that new data and computational tools are used effectively: greater integration across disciplines, improved open science standards and a broader scope of inquiry beyond Western contexts. In doing so, we aim to support more rigorous research and inform the development of more effective policies for safer and more sustainable cities worldwide.