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Criminal behavioral data analysis for recidivation estimation in convicted offenders.
Aman Singh1, Subrajeet Mohapatra1, Madhumita Bhattacharya2
1Department of Computer Science Engineering, Birla Institute of Technology Mesra, Ranchi-835215.
Data in Brief
|June 16, 2022
Summary
Understanding criminal recidivism is key to reducing crime. This study assesses offender behavior to predict future criminal acts, aiding rehabilitation efforts.
Area of Science:
- Criminology
- Psychology
- Sociology
Background:
- Recidivism, the repetition of criminal behavior after release from incarceration, poses a significant challenge to public safety and rehabilitation.
- Assessing offender behavioral features is crucial for understanding and predicting repeated criminal activity.
Purpose of the Study:
- To estimate the initial relapse rate among first-time offenders.
- To identify behavioral and psychological factors associated with recidivism in a specific population.
Main Methods:
- Utilized a dataset of 204 offenders from Jharkhand, India.
- Collected data via questionnaires covering personality traits, family background, socio-demographics, crime details, and jail behavior.
- Employed the HCR-20 risk assessment technique for evaluating criminal behavior.
Main Results:
- The study established a dataset for analyzing patterns and psychological qualities of offenders.
- Behavioral features were identified as indicators for predicting recidivism.
Conclusions:
- The developed dataset provides a valuable resource for criminologists, sociologists, and psychologists.
- Understanding offender characteristics is essential for effective crime prevention and rehabilitation strategies.
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