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<p>Crime is not evenly distributed within a city; rather, it clusters in specific areas. While this spatial concentration is well-documented, most studies focus on individual crime types, overlooking how different crimes co-occur. Addressing this gap, this study examines spatial co-occurrence patterns of crimes in New York City from 2008 to 2018. By constructing a crime network, it identifies “brokerage” crimes that connect distinct crime groups. The analysis explores both the clustering of similar offenses and connections between crimes of differing severity, drawing on theories such as repeat victimization and the disorder–crime relationship. Using betweenness centrality, the study highlights crimes like prostitution, drug offenses, and robbery as key bridging offenses. These brokerage crimes, though less frequent, are strongly associated with higher levels of violent and property crime. The findings suggest that targeting such offenses could be crucial for disrupting broader crime patterns and inform more proactive law enforcement strategies.</p>

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Understanding the Spatial Co-Occurrence of Different Crime Types and Brokerage Crime in NYC Block Groups

  • 期刊论文

  • 发表日期：

    2026年2月4日

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  • Young-An Kim,
  • Keungoui Kim

摘要

Crime is not evenly distributed within a city; rather, it clusters in specific areas. While this spatial concentration is well-documented, most studies focus on individual crime types, overlooking how different crimes co-occur. Addressing this gap, this study examines spatial co-occurrence patterns of crimes in New York City from 2008 to 2018. By constructing a crime network, it identifies “brokerage” crimes that connect distinct crime groups. The analysis explores both the clustering of similar offenses and connections between crimes of differing severity, drawing on theories such as repeat victimization and the disorder–crime relationship. Using betweenness centrality, the study highlights crimes like prostitution, drug offenses, and robbery as key bridging offenses. These brokerage crimes, though less frequent, are strongly associated with higher levels of violent and property crime. The findings suggest that targeting such offenses could be crucial for disrupting broader crime patterns and inform more proactive law enforcement strategies.