Nicole Rogers

Author: Nicole Rogers | Major: Data Science | Semester: Fall 2023

Nicole Rogers is a senior pursuing her BS in Data Science under the College of Engineering. Her research mentor Dr. Jeff Gruenewald serves as Director of the Terrorism Research Center and is a Professor in the Department of Sociology & Criminology. Rogers received funding for the Spring and Fall Semesters of 2023.

Data science, a multidimensional field with varied definitions, has always, for me, been irrevocably woven into the art of storytelling. In my opinion, data are more than numbers but narratives waiting to be told. As I approach my final semester my reflections stray away from the lectures and mathematical concepts and gravitate instead towards the stories exposed in my exploration in applying data science to the complexities of the social world. Throughout my collegiate career I have used data science tools to give a new understanding of the world around me.

My research journey started in the fall of 2022 when I joined the Terrorism Research Center (TRC) through an internship with the Crime and Security Data Analytics Lab (CASDAL). CASDAL works to advance the TRC’s goal of leveraging social science and data analytics to inform evidence-based policies and promote safer communities. During my time at CASDAL, I balanced engaging with public interest initiatives with the application and growth of my technical expertise. Inspired and fueled by this blend, I was inspired to delve deeper through a research project.

My work looks at applying crime analysis to Little Rock, Arkansas, a city with historically high levels of crime. Titled “A Spatiotemporal Analysis of Violent Crime in Little Rock from 1999-2022,” my study delved into the intricate details of aggravated assaults and homicides at a micro-level spatial scale over a 23-year period. Little Rock Police Department, with over two decades of historical crime data, provided a distinctive longitudinal scope. The crime data of the past few years (2014 to present) are publicly accessible via the city’s data portal. Data from 1999 through 2013 were accessed via a memorandum of understanding. The study centered on violent crime, comprising a total of 45,000 incidents involving aggravated assaults and homicides.

As crime analysis as a field has evolved, microlevel approaches to understanding crime have become more prevalent. The smaller units of analysis provide a more nuanced understanding of where, and potentially, why crime occurs within a city. Microlevel approaches to crime analysis are beneficial as they facilitate targeted intervention strategies, crime pattern recognition, community policing, and resource allocation. For this analysis I focused on streets and street segments (hundred blocks) and aggregated the crimes across 23 years by these units.

The microlevel spatial analysis told a story of Little Rock’s profoundly uneven violent crime distribution. In the realm of crime analysis, the 80/20 rule is a theoretical concept for uneven crime distribution. This rule suggests that a large majority of incidents occur at a small minority of locations–specifically that 80% of crimes occur at 20% of locations. In the case of Little Rock, the concentration of violent crime is even more pronounced, with 80% of historical violent crimes concentrated on a mere 14% of the streets. Digging deeper, a mere 1% of the streets accounted for a staggering 27% of violent crimes. Breaking down the streets into hundred blocks revealed that only 8 street segments were responsible for 5% of the violent crimes. A half mile section along Colonel Glenn Road had 535 violent incidents. That is over 1% of the total violent crimes in Little Rock for the 23-year time period. The next highest street segments had 351, 275, and 258 violent crimes. These metrics, derived from the microlevel analysis, underscore the substantial historical concentration of violent crime in Little Rock, Arkansas.

Beyond the analytical aspect, effective communication of results was a pivotal focus of my project. Despite the challenge of transitioning mentors in my second semester, this shift provided a clear understanding of the importance of articulating results and the underlying process. Along with my analysis, I created an infographic that was sent to the police department and documented the research process comprehensively, facilitating potential replication for other cities and crime types.

With the support of the Honors College Research Grant, I actively participated in every facet of a crime analysis project and the overall research process. This experience has given me tools that extend beyond academia and ones that I will continue to leverage in my professional career. As I approach the conclusion of my BS in Data Science, I am excited to continue to explore and uncover the narratives concealed in data sets. My aim is not only finding the stories data tell, but to use these findings to inform and support positive social change.