Spatiotemporal Approach To Social Disorganization And Crime: Evidence From Austin City's Changing Population

• In Event: Social Disorganization Theory: Places, Spaces, and Time

Abstract

This study thoroughly examines the increased population mobility in Austin City and its potential impact on crime patterns within local communities. Drawing upon the Social Disorganization Theory, we analyze demographic shifts and crime patterns within the framework of societal breakdown, with a specific focus on Austin City's socioeconomic landscape and spatiotemporal dynamics. From 2000 to 2020, our study shifts in population characteristics and crime patterns across various communities in Austin City, emphasizing the importance of capturing spatial correlations. Through hotspot and kernel density analyses, we identify density fluctuations that reflect changes in crime patterns resulting from demographic transformations over time. Also, employing spatial lag models and error models to control spatial autocorrelation, we investigate how evolving population characteristics within communities influence local crime rates. The research aims to examine the impact of population influx and outflow on crime rates and types in Austin City, offering actionable insights for urban planning, public policy, and law enforcement. Our primary hypothesis suggests that areas experiencing high population turnover tend to exhibit higher crime rates, with this phenomenon interacting with community characteristics through regional autocorrelation.

Authors

• Minyeong Yoon, University of Texas at Dallas

• Dohyo Jeong, University of Texas at Dallas