O SooHyun
Dados Biográficos
| ID | 6804526 |
|---|---|
| NOME | O SooHyun |
| SOBRENOME | O SooHyun |
| ASSINATURA | SOOHYUN O |
| AFILIAÇÕES | University of South Florida Sarasota–Manatee |
| VERIFICADO | Não |
| TOTAL DE OBRAS | 10 |
| TOTAL DE CITAÇÕES | 4 |
| TOTAL COMO AUTOR | 10 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2016 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2026 |
| ÍNDICE H | 1 |
Not Just for Adults
This study examines whether crime locations are similar or different for juveniles and adults by comparing the distribution of offenses across land uses and their changes over time. Using 6 years of crime data from Colorado Springs, we calculated rank products for each of 35 land uses, stratified by age group and offense type, and summarized rank stability with interquartile ranges. Findings show both similarities and disparities in the rank orde…
What Do We Know About Hot Pot Spots? Does Who Owns Matter
This study examines how place management practices influence crime distribution at pot shops. We assess whether these practices explain the varying crime levels observed across different pot shops. Using data from Colorado Springs, Colorado, we apply a Poisson distribution to compare expected and actual crime distributions among pot shop owners. Multilevel Poisson regression models are then employed to quantify the extent to which crime variation…
Personalities, Cyber Activities, and Adolescent Cyber Delinquency
This study examines how crime propensity characteristics relate to cyber delinquency directly and indirectly, through crime opportunity. In doing so, it considers propensity by way of different aspects of personality and crime opportunity in the form of a comprehensive set of online activities. Both the direct and indirect relationships are modeled using path analysis in MPlus with the data from 2,015 students from schools in South Korea. Finding…
Improving Recidivism Forecasting With a Relaxed Naïve Bayes Classifier
Correctional authorities require accurate, unbiased, and interpretable tools to predict individuals’ chances of recidivating if released into the community. However, existing prediction models have serious limitations meeting these requirements. We overcome these limitations by applying an established medical diagnostic approach: a relaxed naïve Bayes classifier. Using logistic regression in the form of a naïve Bayes classifier, we estimate the w…
Redefining Recidivism Prediction
This study explores the effectiveness of machine learning algorithms in predicting recidivism, focusing on the impact of race and geographic location variables. Leveraging a dataset from the prisons in Georgia, we assess six algorithms’ forecasting performance, both with and without these key variables. Our findings indicate that geographic location generally enhances predictive accuracy more consistently than race across models. This research hi…
Crime Prevention in the Classroom
This study examines school-based crime prevention tactics using a place management framework in conjunction with deterrence and labeling theoretical perspectives. We examine the effects of four different aspects of place management on student offending and explore whether and how the effects are distinctive for female versus male students. We analyze survey data from students and principals across three waves of the Rural Substance abuse and Viol…
Deviant Identity and Offending
This study examines deviant identity in relation to youth offending by combining items tapping both self-appraisal and reflected appraisal. In particular, using survey data from 3,446 Korean youth across five waves of the Korea Youth Panel Survey (KYPS), findings from group-based trajectory modeling (GBTM) present four distinct offending groups—a high-rate chronic group, stable non-offending group, adolescence-limited group, and declining group. …
Why Your Bar Has Crime but Not Mine
Interpretations of two bodies of crime-place research conflict. Land use and crime studies claim particular facilities increase crime. Risky facilities studies show most places of a single type have little or no crime, but a few of that type have a great deal of crime. How can a facility be generally criminogenic and mostly safe? To resolve this conflict, we make use of the fact that a single owner can own multiple facilities and each owner may h…
Street Codes and Adolescent Violent Victimization at School
This study examines the effects of adherence to street codes on school-based violent victimization. In doing so, it separates street values into two distinct orientations: (1) retaliatory norms, and (2) general toughness norms. We analyze survey data from students across four waves of the Rural Substance Abuse and Violence Project using two-level mixed effects Poisson regression. The model specifies random intercepts across individuals to address…
Crime and land use in Pittsburgh
Crime and land use in Pittsburgh
Street Codes and Adolescent Violent Victimization at School
This study examines the effects of adherence to street codes on school-based violent victimization. In doing so, it separates street values into two distinct orientations: (1) retaliatory norms, and (2) general toughness norms. We analyze survey data from students across four waves of the Rural Substance Abuse and Violence Project using two-level mixed effects Poisson regression. The model specifies random intercepts across individuals to address…
Why Your Bar Has Crime but Not Mine
Interpretations of two bodies of crime-place research conflict. Land use and crime studies claim particular facilities increase crime. Risky facilities studies show most places of a single type have little or no crime, but a few of that type have a great deal of crime. How can a facility be generally criminogenic and mostly safe? To resolve this conflict, we make use of the fact that a single owner can own multiple facilities and each owner may h…
Deviant Identity and Offending
This study examines deviant identity in relation to youth offending by combining items tapping both self-appraisal and reflected appraisal. In particular, using survey data from 3,446 Korean youth across five waves of the Korea Youth Panel Survey (KYPS), findings from group-based trajectory modeling (GBTM) present four distinct offending groups—a high-rate chronic group, stable non-offending group, adolescence-limited group, and declining group. …
Crime Prevention in the Classroom
This study examines school-based crime prevention tactics using a place management framework in conjunction with deterrence and labeling theoretical perspectives. We examine the effects of four different aspects of place management on student offending and explore whether and how the effects are distinctive for female versus male students. We analyze survey data from students and principals across three waves of the Rural Substance abuse and Viol…
What Do We Know About Hot Pot Spots? Does Who Owns Matter
This study examines how place management practices influence crime distribution at pot shops. We assess whether these practices explain the varying crime levels observed across different pot shops. Using data from Colorado Springs, Colorado, we apply a Poisson distribution to compare expected and actual crime distributions among pot shop owners. Multilevel Poisson regression models are then employed to quantify the extent to which crime variation…
Personalities, Cyber Activities, and Adolescent Cyber Delinquency
This study examines how crime propensity characteristics relate to cyber delinquency directly and indirectly, through crime opportunity. In doing so, it considers propensity by way of different aspects of personality and crime opportunity in the form of a comprehensive set of online activities. Both the direct and indirect relationships are modeled using path analysis in MPlus with the data from 2,015 students from schools in South Korea. Finding…
Improving Recidivism Forecasting With a Relaxed Naïve Bayes Classifier
Correctional authorities require accurate, unbiased, and interpretable tools to predict individuals’ chances of recidivating if released into the community. However, existing prediction models have serious limitations meeting these requirements. We overcome these limitations by applying an established medical diagnostic approach: a relaxed naïve Bayes classifier. Using logistic regression in the form of a naïve Bayes classifier, we estimate the w…
Redefining Recidivism Prediction
This study explores the effectiveness of machine learning algorithms in predicting recidivism, focusing on the impact of race and geographic location variables. Leveraging a dataset from the prisons in Georgia, we assess six algorithms’ forecasting performance, both with and without these key variables. Our findings indicate that geographic location generally enhances predictive accuracy more consistently than race across models. This research hi…
Not Just for Adults
This study examines whether crime locations are similar or different for juveniles and adults by comparing the distribution of offenses across land uses and their changes over time. Using 6 years of crime data from Colorado Springs, we calculated rank products for each of 35 land uses, stratified by age group and offense type, and summarized rank stability with interquartile ranges. Findings show both similarities and disparities in the rank orde…
Crime Patterns and Interventions (10 obras) · Psychology (6 obras) · Computer Science (5 obras) · Crime, Illicit Activities, and Governance (4 obras) · Criminology (4 obras) · Social Psychology (4 obras) · Criminal Justice and Corrections Analysis (3 obras) · Developmental psychology (3 obras) · Machine learning (3 obras) · Medicine (3 obras)