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Junghwan Bae

As seen in: Taylor & Francis Online
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Articles by Junghwan Bae

Exploring the spatial dynamics of intra- and inter-racial violence: impact of movement patterns and social interaction

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By Stan Korotchenko, Olga B. Semukhina, Junghwan Bae
| Taylor & Francis Online
Abstract Using 2019 Arlington, Texas, census block group data, this research examines whether human mobility is differentially associated with inter- versus intra-racial assault rates. Negative binomial regressions run on the data comprised of mobile-device traces, police incidents, and community covariates revealed that greater diversity of visitor origins and longer travel distances are associated with higher inter-racial assault rates, whereas longer dwell times are linked to lower rates.
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Are Solo Burglars More Experienced? Differentiating Solo and Group Burglary Offenders by Motivation, Target Selection, and Skill Use

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By Seungmug Lee, Junghwan Bae
| Taylor & Francis Online
ABSTRACT This study examines behavioral and situational differences between solo and group burglary offenders using survey data from incarcerated burglars (N = 284). Logistic regression analyses reveal that solo offenders are more likely to be motivated by subsistence needs, exercise greater care in disposing of stolen property, and select targets based on environmental cues indicating neglect or vacancy.
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How After-Hours Population Composition Affects Crime: Analyzing Resident-Visitor Ratios in Urban Neighborhoods Throughout the Day

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By Stan Korotchenko, Olga B. Semukhina, Christopher Copeland, Junghwan Bae
| Taylor & Francis Online
ABSTRACT This study investigates the relationship between after-hours population composition and neighborhood crime across 164 census block groups in Arlington, Texas. Drawing on routine activity theory, we examine how resident-to-visitor ratios influence crime rates after-work-hours. Using mobile phone tracking data and crime reports for aggravated assault, robbery, and motor vehicle theft, we apply multivariate clustering and negative binomial regression analyses.
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