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, Complex network, Social network, Scientists’ collaboration network, Subgraph structural equivalence, Role

Abstract: Identification of the local structure of scientists’ collaboration network can help understand the cooperative behavior of scientists. Based on complex network subgraph and social network structural equivalence, the subgraph structural equivalence based role identification method was proposed, and applied to the role analysis of the collaboration network involving scientists from complex network research. Using 11 kinds of node-positions in the six 4-node subgraphs, the node-position properties of the scientists’ collaboration 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 correlated with degree, betweenness and closeness centrality measures. The top 20 scientists (degree ranked) were divided into two subgroups, based on the distributions of the relative number of roles. The study provides a quantitative method for role analysis of individual actors in social cooperation networks.