Introduction

Our team name is The Avengers of Data and our project will focus on crime data in New York City, with a particular emphasis on analyzing how socioeconomic and racial factors are correlated with the reporting and police response to crime. Our goal is to highlight how racial profiling affects certain groups in NYC and identify the groups that are more frequently subjected to criminalization

To do this, we have assembled arrest data from five racial groups (Asian, Black, Hispanic, White, and Other) in combination with population ratios in each borough, to visualize racial groups disproportionately affected by policing in New York. Along with our data, our map room holds personal stories and news articles addressing increased policing during the Black Lives Matter Movement. This supplemental history allows users to view personal stories and narratives revealing targeted policing and criminalization of marginalized communities.

Our map is targeted towards the general public with hopes that our insight will further educate users about the severity of targeted policing and hopefully inspire individuals to take action in the fight against racial injustice and its correlation to the arrest phenomena.

Meet the Team!

Christina Cha	Cynthia Gong	Daniel Fouladian	Kristina Thabet
Designer	Data Analyst	Data Analyst	Writer / Data Analyst
Christina is a third year majoring in Business Economics and minoring in Digital Humanities. Professionally, she is interested in marketing, specifically product marketing, for the tech and entertainment industry. In her free time, she loves spending time with her cat and family.	Cynthia is a third year studying Statistics and Digital Humanities. She’s interested in real estate, urban planning, and the entertainment industry. In her free time, she enjoys taking care of her houseplants and painting landscape scenery	Daniel Fouladian is a senior pursuing a B.A in Psychology with a minor in Digital Humanities (2022). He continues to succeed academically as he was born deaf and wears a Cochlear Implant to hear. He hopes he can inspire many more to overcome their obstacles and hardships. In his free time, he loves to play sports and create using graphic design.	Kristina is a senior pursuing a BS in Economics with a minor in Digital Humanities. Professionally, she is interested in social media marketing and fashion styling. In her free time, she loves sourcing vintage clothing and relaxing with friends and family.

Overview

Black Lives Matter is an international social movement, beginning in 2013, dedicated to not only ending police violence, but disrupting state-sanctioned violence against Black People. In May of 2020, the Black Lives Matter movement gained extreme attention after the police killing of George Floyd, a Black man in Minneapolis, Minnesota. Protesters and organizers gathered day-after-day to build local power and intervene against violence inflicted on Black communities. Our New York Crime data spans from May of 2020 to July 2020, shedding light on not only the types of arrests happening during this time, but what race the police officer perceived the perpetrator to be. As we focus our data on this time period, we hope to gain a better understanding of racially targeted police violence that occurs in New York. We also will see numeric values of perpetrator arrests along with their race, revealing the many protesters, particularly those of color, who were arrested at these protests for fighting against racism and anti-black violence.

Methodology

We will be using web mapping as our methodology of inquiry to provide a more comprehensive and interactive investigation into our data. Contextualizing arrest data and crime statistics can often be difficult without seeing the location of where these crimes occured. This is because crime itself tends to be a location-based phenomenon, where certain locales tend to be more prone to crime than others. As a result, it is important we visualize our data points on a map.

We created a multi-layered map that provides a narrative on racial profiling by NYPD as well as a general comparison between crime and racial background. The main feature of the map is to display demographic information for each neighborhood and compare it to the density of arrests in that neighborhood by racial background. Arrests are pinned onto the map by markers, enabling viewers to understand the arrest patterns by NYPD. Likewise, our map also includes pins highlighting the location of major BLM protests to help contextualize the spatial environment of our analysis.

Importance of Our Project

Our project provides both quantitative and qualitative data of New York arrested during June of 2020. This was a peak point of the Black Lives Matter protests, BLM being an international social movement, beginning in 2013, dedicated to not only ending police violence, but disrupting state-sanctioned violence against Black People. In May of 2020, the Black Lives Matter movement gained extreme attention after the police killing of George Floyd, a Black man in Minneapolis, Minnesota. Protesters and organizers gathered in the streets in hopes of building local power and intervening against violence inflicted on Black and marginalized communities.

Project Scope

Our map is at the city-level and focuses on NYC and its five boroughs. At the technical level, we embedded Leaflet into our JavaScript code to create an interactive map of criminal activity in New York City. We utilized HTML to create the skeleton structure of our website and CSS to add design elements. GitHub was used to merge our individual code blocks and host our website.

Data

NYC Arrest Data

This dataset contains a list of every single arrest in NYC up until the end of 2020. Variables of interest include the perpetrator race as well as exact coordinates of where the arrest occured. To create our dataset used for the map, we queried all the arrests within the month of June 2020 and exported the data as a CSV file. The data was then geocoded using JavaScript. Each category of data delineated by perpetrator_race created a separate layer on the map.