The salience of neighborhoods in shaping crime patterns is one of sociology’s most robust areas of research. One way through which neighborhoods shape outcomes is through the creation and maintenance of social networks, patterns of interactions and relationships among neighborhood residents, organizations, groups, and institutions. This paper explores the relationship between network structures generated through acts of co-offending—when two or more individuals engage in an alleged crime together—and patterns of neighborhood gun violence and gun availability. Using arrest data from New York City, we create co-arrest networks between individuals arrested in the city between 2010 and 2015. We analyze these network patterns to, first, understand the overall structure of co-offending networks and, then, assess how they impact neighborhood levels of gun violence and gun availability. Results show that local and extra-local networks play a central role in predicting neighborhood levels of shootings: neighborhoods with a greater density of local ties have higher shootings rates, and neighborhoods that share social ties have similar rates of violence. In contrast, the network dynamics involved in gun recoveries are almost entirely local: co-offending patterns within neighborhoods are strongly associated with the level of gun recoveries, especially the clustering of co-offending networks indicative of groups. Contrary to previous research, spatial autocorrelation failed to predict either shootings or gun recoveries when demographic features were considered. Social-demographic characteristics seem to explain much of the observed spatial autocorrelation and the precise measurement of network properties might provide better measurements of the neighborhood dynamics involved in urban gun violence.

中文翻译：

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邻里犯罪网络对于枪支暴力和枪支供应的重要性


社区在塑造犯罪模式方面的重要性是社会学最有力的研究领域之一。社区塑造成果的一种方式是创建和维护社区居民、组织、团体和机构之间的社交网络、互动模式和关系。本文探讨了通过共同犯罪行为（当两个或更多人一起参与涉嫌犯罪时）产生的网络结构与邻里枪支暴力和枪支供应模式之间的关系。利用纽约市的逮捕数据，我们在 2010 年至 2015 年间在该市被捕的个人之间创建了共同逮捕网络。我们分析这些网络模式，首先了解共同犯罪网络的整体结构，然后评估它们如何影响社区枪支暴力水平和枪支供应情况。结果表明，本地和本地外网络在预测社区枪击事件水平方面发挥着核心作用：本地关系密度较高的社区的枪击率较高，而具有社会关系的社区的暴力发生率相似。相比之下，枪支追回所涉及的网络动态几乎完全是本地的：社区内的共同犯罪模式与枪支追回的水平密切相关，特别是表明群体的共同犯罪网络的集群。与之前的研究相反，当考虑人口特征时，空间自相关无法预测枪击事件或枪支追回情况。 社会人口特征似乎可以解释大部分观察到的空间自相关性，而网络属性的精确测量可能可以更好地测量城市枪支暴力中涉及的邻里动态。