Big Data Promotes Social Governance Toward “Social Intelligence”--The Case of Community Corrections

Abstract

This paper discusses the application of big data in community corrections and analyzes its contribution to improving the effectiveness of governance, focusing on enhancing the science and effectiveness of community corrections strategies. Using a Random Forest Model and Deep Reinforcement Learning Network, the dangerousness of community correctional officers is analyzed and corresponding strategies are proposed. The random forest model achieved 99.92% accuracy in predicting community correctional officers’ delinquency, and 99.79% in predicting recidivism. The deep reinforcement learning model performs well in correctional strategy recommendations, with an accuracy rate of more than 90% for different strategies. The application of big data technology effectively improves the formulation and implementation of community correctional strategies, which positively impacts modernizing social governance.

Keywords

• big data
• community correction
• random forest model
• social governance
• 97b10