国际合作网络结构与高被引论文产出的关系研究

The Relationship between the Network Structure and Countries of Highly-cited Papers in International Collaboration Network

基于2007-2016年Web of Science的国际合作论文数据的文献计量,对中国的国际科研合作进行统计描述。构建国际合作网络,描述全局网络统计特征,发现合作网络与经典小世界和无标度网络模型并不完全一致。以度中心性、接近中心性、特征向量中心性、结构洞约束和连接强度作为节点的网络结构的度量指标,采用负二项回归模型对网络结构和高被引论文产出之间的关系进行分析。回归分析的结论认为:特征向量中心性是促进高被引论文产出最重要的影响因素,其次是连接强度;结构洞约束对高被引论文产出有显著阻碍效应,其次是度中心性;接近中心性并不带来显著优势。

This study describes the international collaboration of China based on bibliometric data of internationally co-authored papers from web-of-science during 2007-2016, from which the international collaboration network is generated. The global network properties are calculated, indicating the network is not exactly the same as small-world model or scale-free model. The network structure properties of countries, including degree centrality, closeness centrality, eigenvector centrality, constraint and tie strength,are measured. The relationship between the network structure and highly cited papers is tested in negative binominal regression model. The results of regression analysis are stated as follows: eigenvector centrality is the most influential factor in promoting highly cited papers, and the next is tie strength;constraint significantly hampers the output of highly cited papers, and the next is degree centrality;the effect of closeness centrality is not significant.