犯罪网络构建及其时空分析——以入室盗窃为例

提出了一种基于时空影响范围的网络构造方法，构造了一种基于节点影响强度的犯罪传输网络，并引入复杂网络的度、平均度、聚集系数等特征参数分析犯罪传输网络。提取了犯罪预测过程中需要关注的重要节点，分析了其时间分布和空间分布特性，研究结果表明:（1）近邻的时空单元的犯罪率具有一定的关联关系。其中，节点的出度与入度具有正相关性，因此可以引入邻居时空单元的犯罪密度以量化和分析犯罪规律。（2）节点的度分布具有无标度特性，犯罪较少的小区也可能出现度较大的节点，而节点的度与未来犯罪率具有较大的关联性。因此，即便犯罪率较低的小区也要关注节点的度变化情况。（3）犯罪聚集系数大小与未来犯罪率的变化具有一定的关联性，较高的聚集系数意味着未来犯罪状态的变化。

Construction and Spatial-Temporal Analysis of Crime Network: A Case Study on Burglary

A network construction method based on temporal-spatial influence is proposed. Then a crime transmission network based on the impact strength of nodes is constructed based on the method. The characteristic parameters of complex networks are introduced. The concept of degree, average degree, clustering coefficient and analysis of criminal network are carried out. The results show that degree of the nodes are related to the future crime rate, which can be used in crime forecasting; Distribution of node's degree has no scaling property. Burglary can also occur within areas rarely be infringed. And the degree of the node is closely related to the crime rate future. Therefore, even if the crime rate is relatively low, the district should also pay attention to the changes of node's degree; Coefficient of crime aggregation has predictability to the future crime rate. Higher aggregation coefficient means the state of crime may change in the future. The spatial-temporal characteristic of important nodes in crime prediction was analyzed at last.