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“On to the next one:” Using social network data to inform police target prioritization

机译:“转到下一个:”使用社交网络数据告知警察目标优先级

摘要

As part of the portfolio of strategies used to achieve crime reductions, law enforcement agencies routinely establish a list of offenders to be targeted as priorities. Rarely considered, however, is the fact that targets are embedded in larger social networks. These networks are a rich resource to be exploited as they facilitate: 1) efficient prioritization by understanding which offenders have access to more resources in the network, and 2) assessments of the impact of intervention strategies. Drawing from law enforcement data, the personal networks of two mutually connected police targets from a mid-size city in British Columbia, Canada were constructed. Results show that of the 101 associates in their combined network, 50 percent have a crime-affiliated attribute. The network further divides into seven distinct communities, ranging from four to 25 members. Membership to these communities suggests how opportunities, criminal and non-criminal, form and are more likely to occur within one’s immediate network of associates as opposed to the larger network. As such, seven key players that have the highest propensity to facilitate crime-like behaviours are identified via a measure of “network capital,” and located within the communities for informed target selection.
机译:作为用于减少犯罪的策略组合的一部分,执法机构通常会建立一个以犯罪者为目标的清单。但是,很少考虑将目标嵌入较大的社交网络中。这些网络是一种可利用的丰富资源,因为它们可以促进:1)通过了解哪些罪犯可以使用网络中的更多资源来进行有效的优先级排序,以及2)评估干预策略的影响。根据执法数据,构建了来自加拿大不列颠哥伦比亚省一个中型城市的两个相互关联的警察目标的个人网络。结果显示,在他们的合并网络中的101名同伙中,有50%具有犯罪从属属性。该网络进一步分为七个不同的社区,成员范围从4到25。这些社区的成员资格表明,犯罪的和非犯罪的机会是如何形成的,并且更有可能在一个员工的直接网络中而不是在更大的网络中发生。因此,通过衡量“网络资本”来确定七个最有可能促进类似犯罪行为的关键参与者,并将其置于社区内以供明智选择目标。

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    Hashimi Sadaf;

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  • 年度 2015
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