方法对比
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| 风险地形建模× | 法律判例的网络分析× | |
|---|---|---|
| 领域 | 法证学 | 法证学 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份 | 2011 | 2011 |
| 提出者≠ | Joel Caplan | James Fowler |
| 类型≠ | Geographic information systems and crime science method | Network science and legal informatics method |
| 开创性文献≠ | Caplan, J. M., Kennedy, L. W., & Miller, J. (2011). Risk terrain modeling: Brokering criminological theory and GIS methods for crime forecasting. Journal of Research and Practice in Criminal Justice, 17(1), 56-69. link ↗ | Lupo, G., & Bailey, J. (2014). Artificial intelligence and legal practice. Academic Press. link ↗ |
| 别名 | environmental criminology, RTM analysis, crime risk mapping | citation network analysis, legal precedent mapping, case law graph analysis |
| 相关 | 3 | 3 |
| 摘要≠ | Risk Terrain Modeling (RTM) is a geospatial crime prediction method that identifies high-risk locations by analyzing environmental and geographic features that attract or facilitate crime. Developed by Joel Caplan, Lichen Kennedy, and James Miller in 2011, RTM bridges environmental criminology theory with geographic information systems (GIS) to create predictive risk maps. Unlike methods that predict offender location (e.g., geographic profiling), RTM predicts where crimes are likely to occur based on terrain characteristics, infrastructure, and social environmental factors. | Network analysis of case law applies graph-theoretic and network science methods to study the structure and dynamics of legal precedent systems. Developed systematically by James Fowler and colleagues in 2011, this method treats legal citations as directed edges in a network where nodes represent court decisions and edges represent precedent relationships. By analyzing the topology of these networks, researchers uncover patterns in how law evolves, which precedents are most influential, and how legal doctrine spreads across jurisdictions. |
| ScholarGate数据集 ↗ |
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