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The near repeats of gun violence using acoustic triangulation data

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A Correction to this article was published on 14 March 2019

This article has been updated

Abstract

Near repeat signatures of gun violence have been generated exclusively from incidents reported to or discovered by police. However, many gun crimes go unreported. In Trenton NJ, it is believed as many as 60% of all such cases do not come to the police’s attention. This research explores near repeat qualities of gun-related violent crime in Trenton using an underutilized dataset, sounds of gunshots from ShotSpotter, allowing us to capture both reported and unreported gun-related violent crime. When examining reported and unreported gun violence, compared to solely relying on reported cases, near repeat signatures are smaller geographically and exhibit larger and more consistent statistically significant effects across temporal bands. Near repeat chains also occur more frequently and include more events. We caution against only using reported events in near repeat analyses. Improved measures of crime may change the character of near repeat events, research findings, and the operational response.

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Change history

  • 14 March 2019

    Due to an unfortunate oversight an error occured in the sentence “A Bookings Institution report by Carr and Doleac (2016) provides a more scientifically grounded non-reporting estimate of 12% of gunfire incidents.”

Notes

  1. Homicides and assaults where the gun was not actually fired have been removed from this analysis.

  2. In the current study, sensors cover roughly 40% of the city, therefore, our analyses are limited to the areas where there is overlap between the two data sources, police incident reports and acoustic sensor data (Shea 2015).

  3. These days roughly align with the 4th of July and New Years holiday when fireworks are often setoff in celebration. Other holidays such as Halloween were considered, but there were such low rates of fireworks on these days, and a general sense from TPD that these other holidays did not exhibit unusual levels of potential false positives.

  4. There are small number of such cases (< 3%) and when included in the analysis, no significant changes in the results were noted.

  5. While these cut-offs are somewhat arbitrary, changing these criteria would not dramatically affect the results. There are only a handful of cases that occurred around the borders of these cut-offs.

  6. Certainly, there are many non-law enforcement responses to near repeats, some of which may be less constricted by our five block threshold. This bandwidth is measured using Euclidian distance, a truer unit of travel in Trenton’s grid-like layout.

  7. When examining the same location (same XY), duplicates were automatically generated in the Near Repeat Calculator because the software simulates data for these locations regardless of what spatial bandwidth is selected. To adjust for this, we only interpret the first same-location temporal bandwidth generated for each dataset (which started at three block bandwidth intervals) and remove the others. This process removes 64 redundant near repeat estimates from the analysis.

  8. The Near Repeat Calculator measures the distance and time from each point to every other point, leading to a large number of potential pairs. For the current analysis there are 365,085 (855(854)/2) point pairs for the data including ShotSpotter cases, and 57,291 (339(339-1)/2) for those excluding these incidents.

  9. The salience of the same location near repeat may be a product of the improved precision of the ShotSpotter system. If a citizen hears gunfire, they will do their best to source the location, but this is an inherently imprecise process. A shot at one address could be reported to have occurred anywhere along that address range, or beyond.

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Authors and Affiliations

  1. Department of Criminology, The College of New Jersey, PO Box 7718, Ewing, NJ, 08628-0718, USA

    David M. Mazeika

  2. UCLA Police Department, 601 Westwood Pz, Los Angeles, CA, 90095, USA

    Lorena Uriarte

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  1. David M. Mazeika
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  2. Lorena Uriarte
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Correspondence to David M. Mazeika.

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Mazeika, D.M., Uriarte, L. The near repeats of gun violence using acoustic triangulation data. Secur J 32, 369–389 (2019). https://doi.org/10.1057/s41284-018-0154-1

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