Introduction
During the 1990s, the United States saw a great decline in violent crime as the econmy was recovering and the general aging of the population left less people in the typical age rage. However, in New York City, there were some different reasons for such severe decline in crime rates. The city’s econcomy had not yet improved with the rest of the country, and the poorest neighborhoods were struggling with more welfare cuts. As for the aging factor, heavy immigration was bringing younger and younger people to the city, but the decline of crime in New York City was not gradual; it was groundbreaking.
The Broken Windows Theory was introduced by James Q. Wilson and George Kelling. They believed that crime was inevitable when disorder was prominent. Therefore, if a window is broken, people walking by will assume the area is un-cared for. In a city, this problems spreak to graffiti, public disorder, and aggressive panhandling which all lead to invitations for more serious crimes. This theory basically states that crime is contagious.
The city took extreme measures to wash the graffiti off the streets. Painting graffiti was a three-day process where the artist would come paint a base coat and let it dry, then paint the outline of the work, and finally use colors to fill in the lines. Police officers would watch from the first day, and before the graffiti would get to sunlight, it would be gone.
I found this concept extremely interesting and while looking through New York City’s open data, I imagined it would be interesting to analyze in the modern context. Although I could not attain graffiti on broken windows, I found information of graffiti and crime rates.
Hypothesis
I believe there will be a correlation between the time and place graffiti exists similarly to the Broken Windows Theory. New York City, of course, has lost their intensity with cleaning their city, so it will be interesting to see if there are new spikes.
Method
To begin my project, I downloaded graffiti tracking and crime data from NYC in 2019. I was able to view the days the incidents took place and where they took place.
Maps Here’s a link to my maps showing places that were affected by crime and graffiti over 2019 by date: https://public.tableau.com/views/graffitiandcrime/Dashboard1?:display_count=y&publish=yes&:origin=viz_share_link
**Note: Graffiti data goes back further; when viewing the map, make sure you have the dates set the same.
As you can see, crime greatly overtakes the amount of reported graffiti in New York. Because of this, I decided to also include the maps that did not include the dates. This provides a total look at where graffiti and crime overlapped, so we can view the areas that appear more clumped.
Here’s a link to my maps showing places that were affected by crime and graffiti: https://public.tableau.com/views/GraffitiandCrimeMapsNYCwithoutDate/Dashboard1?:display_count=y&publish=yes&:origin=viz_share_link
As we can see, there are clearly areas that have a higher density of both crime and graffiti.
Graphs After looking at the maps, I decided to graph the specific crime and graffiti found per borough (Bronx, Brooklyn, Manhattan, Queens, and Staten Island)
Crime: https://public.tableau.com/profile/sallie7528#!/vizhome/ArrestsperBorough/Sheet3?publish=yes
Graffiti (day it appeared): https://public.tableau.com/profile/sallie7528#!/vizhome/GraffitiperBorough/Sheet4?publish=yes
Graffiti (day it was cleaned): https://public.tableau.com/profile/sallie7528#!/vizhome/CleanedGraffitiperBorough/Sheet5?publish=yes
These graphs were particularly interesting because you could directly compare outbursts of graffiti to the crime, and there did not appear to be much correlation.
Conclusion Although I did not find the most clear information, I still believe there is some correlation. You can definitely watch for spikes in any of the graphs that correlate with one another. If I were to do this project again, I would hope to find open data on more “broken windows” signs, and I would group the crimes to be positive I am looking at specific types of crimes rather than small offenses.
Works Cited:
“3.” The Tipping Point: How Little Things Can Make a Big Difference, by Malcolm Gladwell, CNIB, 2002.