基于子图结构对等的科学家合作网络角色辨识  

Subgraph structural equivalence based role identification of scientists’collaboration network

作　　者：刘亮[1] 韩传峰[2] 缪莉莉[2] 曹吉鸣[2] 姚晓勃[2] 

机构地区：[1]同济大学电子与信息工程学院,上海201804 [2]同济大学经济与管理学院,上海200092

出　　处：《科学学研究》2013年第8期1128-1135,共8页Studies in Science of Science

基　　金：国家自然科学基金资助项目(70871093;91024023);中国博士后科学基金(2012M520935)

摘　　要：辨识科学家合作网络的局部结构可以增进对科学家合作行为的理解。基于复杂网络子图搜索和社会网络结构对等性,提出基于子图结构对等的科学家合作网络角色辨识方法,并应用于复杂网络领域科学家合作网络角色分析中。研究界定了六种4节点子图的11种点位,讨论了复杂网络领域科学家合作网络点位特征,并依据科学合作特性将11种点位分为核心、中介和边缘三类角色;分析发现科学家角色种类的多样性,且其种类数与度、介数和接近性等中心性指标呈正相关关系;基于角色相对数量分布将排名前20位的顶尖科学家分为两个子群体。研究提供了社会合作网络个体行动者角色辨识的定量方法。Identification of the local structure of scientists ＇ collaboration network can help understand the cooperative behavior of scien- tists. Based on complex network subgraph and social network structural equivalence, the subgraph structural equivalence based role i- dentification method was proposed, and applied to the role analysis of the collaboration network involving scientists from complex net- work research. Using 11 kinds of node - positions in the six 4 - node subgraphs, the node - position properties of the scientists＇ collab- oration network were investigated. It was found that the 11 kinds of node - positions can be divided into three categories of roles, i. e. , core, intermediary, and edge. The diversity of the roles of scientists was also found, and the number of role types was positively corre- lated with degree, betweenness and closeness centrality measures. The top 20 scientists （degree ranked） were divided into two sub- groups, based on the distributions of the relative number of roles. The study provides a quantitative method for role analysis of individu- al actors in social cooperation networks.

关 键 词：复杂网络 社会网络 科学家合作网络 子图结构对等 角色 

分 类 号：N94[自然科学总论—系统科学] G31[文化科学]