Mining COVID-19 and NJ Crimes

Ching Yu Huang; Oluwatunmise Alabi; Egan Okumu; Ibarra Joussef

doi:10.1145/3624875.3624887

Mining COVID-19 and NJ Crimes

Ching Yu Huang
, Oluwatunmise Alabi
, Egan Okumu
, Ibarra Joussef

Computer Information Systems

Kean University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The COVID-19 pandemic which took the world by storm in 2020 had a profound impact on societies across the world. New Jersey was not immune to the crisis. Between the confusion-induced panic of the unknown surrounding the pandemic, the mass layoffs, the lockdowns, and the growing economic pains, New Jersey experienced a spike in crime. This research study aimed to explore the relationship between the COVID-19 pandemic and crime rates in New Jersey counties during the year 2020, while also comparing the crime rates of 2020 to the previous year. Using publicly available data on COVID-19 case cases [1] and crime rates from official government sources [2] [3], we deployed crucial data mining techniques such as outlier detection and the Pearson Correlation Coefficient to investigate any potential links between these two variables. It was concluded that there is a significant correlation between the effects of COVID and certain crime rates in New Jersey counties. Furthermore, it was determined there was a significant change in crime rates from 2019 to 2020 which can be attributed to the Covid-19 pandemic.

Original language	English
Title of host publication	MISNC 2023 - 10th Multidisciplinary International Social Networks Conference
Publisher	Association for Computing Machinery
Pages	67-73
Number of pages	7
ISBN (Electronic)	9798400708176
DOIs	https://doi.org/10.1145/3624875.3624887
State	Published - 4 Sep 2023
Event	10th Multidisciplinary International Social Networks Conference, MISNC 2023 - Phuket, Thailand Duration: 4 Sep 2023 → 6 Sep 2023

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	10th Multidisciplinary International Social Networks Conference, MISNC 2023
Country/Territory	Thailand
City	Phuket
Period	4/09/23 → 6/09/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 16 Peace, Justice and Strong Institutions

Keywords

COVID-19
Crime
Data Mining
Data Visualization
MatPlotLib
Outlier Detection
Pandemic
Pearson Correlation Coefficient
Python
SQL
SciPy

Access to Document

10.1145/3624875.3624887

Cite this

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title = "Mining COVID-19 and NJ Crimes",

abstract = "The COVID-19 pandemic which took the world by storm in 2020 had a profound impact on societies across the world. New Jersey was not immune to the crisis. Between the confusion-induced panic of the unknown surrounding the pandemic, the mass layoffs, the lockdowns, and the growing economic pains, New Jersey experienced a spike in crime. This research study aimed to explore the relationship between the COVID-19 pandemic and crime rates in New Jersey counties during the year 2020, while also comparing the crime rates of 2020 to the previous year. Using publicly available data on COVID-19 case cases [1] and crime rates from official government sources [2] [3], we deployed crucial data mining techniques such as outlier detection and the Pearson Correlation Coefficient to investigate any potential links between these two variables. It was concluded that there is a significant correlation between the effects of COVID and certain crime rates in New Jersey counties. Furthermore, it was determined there was a significant change in crime rates from 2019 to 2020 which can be attributed to the Covid-19 pandemic.",

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Huang, CY, Alabi, O, Okumu, E & Joussef, I 2023, Mining COVID-19 and NJ Crimes. in MISNC 2023 - 10th Multidisciplinary International Social Networks Conference. ACM International Conference Proceeding Series, Association for Computing Machinery, pp. 67-73, 10th Multidisciplinary International Social Networks Conference, MISNC 2023, Phuket, Thailand, 4/09/23. https://doi.org/10.1145/3624875.3624887

Mining COVID-19 and NJ Crimes. / Huang, Ching Yu; Alabi, Oluwatunmise; Okumu, Egan et al.
MISNC 2023 - 10th Multidisciplinary International Social Networks Conference. Association for Computing Machinery, 2023. p. 67-73 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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KW - Python

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Mining COVID-19 and NJ Crimes

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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