基于共同犯罪的犯罪人地域关系网络的空间演化及其影响因素——以北京市诈骗案件为例

doi:10.18306/dlkxjz.2020.05.008

Abstract

Abstract:

A series of studies have been conducted on the phenomenon of co-offending from the aspects of relationship and relationship structure of offenders, but there is a lack of stability analysis on the regional relationship between offenders. Based on the data of the street fraud cases in Beijing in 2005, 2010, and 2014, this study constructed a regional relation network model of offenders based on the principle of social network, and analyzed the structural characteristics and changing trend of the regional relation network of offenders participating in co-offending by means of network analysis. The main results are as follows. The spatial distribution of origins of offenders participating in the co-offending in Beijing was gradually concentrated, and a pattern of coexistenting multicenters was formed with North China as the main area. The small-world effect of regional relation network of offenders gradually strengthened and developed from power-law distribution mode to exponential distribution mode. Among the offenders who participated in the co-offending, the influence of offenders from Beijing gradually decreased, while that of offenders from Hebei Province gradually increased. The cohesive subgroup structure of the regional relation network of offenders gradually polarized, and a few offender regional subgroup structures that are closely related to co-offending appeared. This study also explored the reasons for the existence and evolution of the cross-area co-offending network from the perspectives of social relation reconstruction and subculture of floating population. The results of this study have some implications for the further research on the relationship pattern of the offenders' co-offending.

Key words: fraud crime, regional relationship network, comparative analysis of changes, social network analysis, Beijing

ZHU Guanyu, CHEN Peng. Spatial evolution and influencing factors of criminals’ cross-area co-offending network: An example of fraud in Beijing[J].PROGRESS IN GEOGRAPHY, 2020, 39(5): 792-803.

Figures/Tables 9

Fig.1

Tab.1

Main indicators of social network analysis"

指标名称	表达式	表达式解释	参数解释
网络密度(D)	$D = 2 M Z (Z - 1)$	反映网络中节点之间关系的密集程度	M表示网络中的边数,Z为网络中节点的数量
聚集系数(C)	$C i = 2 E i k i (k i - 1)$	反映图中节点之间聚集成团的程度	E_i为k_i个节点间相互连接的边数
度数中心度(C_D)	$C D (i) = ∑ j = 1 N a ij$	反映节点在网络中的重要性程度	a_ij为表示社会网络关系的矩阵,节点v_i与v_j之间有关系则赋值为1,否则为0
中介中心度(C_B)	$C B (i) = ∑ j = 1; k = 1; j ≠ k ≠ i N N jk (i) N jk$	测量网络中所有最短路径中经过某一节点的数量比例,反映该节点对资源的控制程度	N_jk表示节点v_j和v_k之间的最短路径条数;N_jk(i)表示节点v_j和v_k之间的最短路径经过节点v_i的条数
强度中心度(C_S)	$C S (i) = ∑ w ij$	测量节点所有关联的关系的权重的集合,反映节点考虑连接关系权重的重要性程度	N_i表示节点v_i的相邻节点集合;w_ij表示连接节点v_i和节点v_j的关系权重

Tab.1

Fig.2

Tab.2

Fig.3

Tab.3

Tab.4

Fig.4

Fig.5

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年份	Z	M	D	Avg.D	C₁	C₂	L	C₁/L
2005	151	485	0.0428	6.4238	0.6240	0.0444	2.6519	0.2353
2010	199	988	0.0501	9.9296	0.6000	0.0500	2.6296	0.2282
2014	203	4241	0.2068	41.7833	0.7936	0.2067	1.9652	0.4038

年份	拟合函数
年份	幂次函数	指数函数
2005	P(k)=2.9562k^-1.353,R²=0.9013	P(k)=0.341e^-0.066k,R²=0.6680
2010	P(k)=3.4725k^-1.173,R²=0.8809	P(k)=0.5329e^-0.06k,R²=0.8668
2014	P(k)=5.7008k^-0.849,R²=0.5741	P(k)=1.3899e^-0.031k,R²=0.8932

排序	点度中心度				中介中心度				强度中心度
排序	2005年	2010年	2014年		2005年	2010年	2014年		2005年	2010年	2014年
1 2 3 4 5 6 7 8 9 10	北京 (85) 齐齐哈尔 (36) 沧州 (23) 牡丹江 (22) 哈尔滨 (21) 菏泽 (19) 保定 (19) 衡水 (18) 呼伦贝尔 (17) 张家口 (17)	北京 (86) 张家口 (86) 承德 (76) 石家庄 (46) 邯郸 (45) 保定 (38) 沧州 (36) 德州 (35) 信阳 (32) 重庆 (31)	保定 (133) 张家口 (124) 承德 (118) 北京 (117) 齐齐哈尔 (111) 徐州 (106) 济宁 (105) 沧州 (104) 邢台 (104) 咸阳 (101)		北京 (0.543) 齐齐哈尔 (0.064) 牡丹江 (0.052) 沧州 (0.048) 衡水 (0.043) 沈阳 (0.040) 南平 (0.026) 太原 (0.025) 广州 (0.025) 邯郸 (0.024)	北京 (0.275) 张家口 (0.226) 承德 (0.105) 石家庄 (0.062) 保定 (0.048) 沧州 (0.044) 达州 (0.042) 菏泽 (0.041) 信阳 (0.041) 六安 (0.036)	北京 (0.068) 保定 (0.055) 咸阳 (0.042) 张家口 (0.038) 徐州 (0.036) 湛江 (0.035) 齐齐哈尔 (0.032) 廊坊 (0.024) 河池 (0.024) 承德 (0.024)		北京 (1612) 衡水 (879) 齐齐哈尔 (870) 德州 (862) 呼伦贝尔 (733) 延边 (700) 南平 (700) 秦皇岛 (301) 保定 (259) 咸宁 (225)	承德 (669) 北京 (656) 保定 (606) 张家口 (556) 聊城 (465) 沧州 (439) 潜江 (342) 宜昌 (331) 牡丹江 (316) 德州 (306)	呼伦贝尔 (1378) 绵阳 (1338) 廊坊 (1297) 沧州 (1271) 邯郸 (1244) 鹤岗 (1212) 保定 (270) 北京 (237) 张家口 (229) 齐齐哈尔 (225)

Spatial evolution and influencing factors of criminals’ cross-area co-offending network: An example of fraud in Beijing

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