When, and in what communities are youth the most disruptive NYC? In order to address this research question, I used 311 complaints of “disorderly youth” between 2015 and 2020 to create a dashboard with three visualizations.
The first visualization addresses the “where” question by mapping all available geocoded “disorderly youth” complaints across the five boroughs. Each dot represents the location of a single report of disorderly youth made via phone or online. Orange dots correspond to complaints made from residential buildings and houses, purple to complaints from stores or other commercial spaces, and pink for complaints of disorderly youth on streets or sidewalks. Hover over any individual dot to see a description of the complaint and the address from which the call was made. Drag the bar at the bottom of the map to limit the visual to particular years, or click on the various colors to limit the visual by location of complaint.
The second and third visualizations cover the timeframe and relative volume of 311 complaints about disorderly youth, or the “when” part of the question. The line chart in the upper right corner displays the number of complaints by location type over the last five years, illustrating a clear downward trend in disorderly youth 311 complaints over the last five years. The stacked bar chart in the bottom right corner depicts disorderly youth complaint volume by month. Hover over any of the color blocks to see the number of complaints made in the associated month at each location type. Notice the clear peak in call volume during the summer months.
The audience with the clearest use case for these visualizations are public safety officials in New York City – the police department, in particular. As the department responsible for responding to complaints of disorderly youth, NYPD could use these data to inform street-level policing strategy. NYPD could theoretically develop predictive modeling to preempt such low-level disturbances by considering historical patterns of 311 disorderly youth complaints. This data set is not, however, a strong candidate to achieve this end given the wealth of geo-coded crime-related data collected by NYPD, and the volume of data detailed data required to build reliable predictive models. Therefore, I’d recommend non-crime related applications of this analysis. For example, the Mayor’s Disconnected Youth Taskforce, was created to help the most vulnerable young New Yorkers — those who do not finish school, those who are not in the workforce or those who are involved with the criminal justice system. The Task Force could use the data to identify when and where to build relationships with the individuals it’s trying to serve. These data could also be useful to community-based public safety efforts dedicated to keeping neighborhoods and local streets safe, or truant officers.
The most pivotal design decision I made was switching from 311 service requests about lead to those about “disorderly youth”. After building several different visualizations with the lead data set, I was still unable to create something compelling because of a lack of variation in the data (nearly every record was a request for a lead test kit, with the same descriptor and resolution time). Disorderly youth proved much easier to visualize and cull insight from because it included multiple types of complaints, and not JUST lead testing kit requests. With longitude and latitude already provided, using a map to address the “where” of disorderly youth was an obvious choice. The line chart was also the obvious choice for longitudinal analysis and the stacked bar chart to show seasonal fluctuations in call volume, emphasizes the total number of complaints over a year with each stacked bar. I selected the brightest colors with the highest contrast, as disorderly youth is never quiet. I included them as one dashboard so they could be viewed simultaneously as one continuous story.
If I could expand the scope of this research, I would introduce additional data sources, as the 311 data doesn’t have much depth. I would like to compare the 311 disorderly youth complaints to police reports of disturbances or petty theft at the same time and location to look for overlapping reports. First, I would need to locate a crime data set with location and and time of submissions.
This entry is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International license.
