高被引华人科学家知识网络的空间结构及影响因素

Spatial structure and influencing factors of knowledge network of highly cited Chinese scientists

知识网络的空间结构特征与影响因素是经济地理学探讨的热点议题之一,以往研究侧重于产业案例的分析,主要关注国家和城市层面的知识网络,而对科学家等个人层面的网络研究较为缺乏。以2014—2015年全球高被引科学家为原始数据,筛选出高被引华人科学家,并基于Web of Science数据库,检索高被引华人科学家之间合著论文的数据构建知识网络,借助社会网络分析方法对高被引华人科学家知识网络的空间结构进行分析;并运用负二项回归模型,从地理邻近性、社会邻近性、制度邻近性3个维度,探讨高被引华人科学家知识网络的影响机制。研究发现:①高被引华人科学家知识网络存在核心-边缘结构特征,且具有小世界网络的网络特征;②此知识网络呈现"小集聚大分散"的空间结构特征,地理邻近性作用明显;③高被引华人科学家知识网络形成过程中会受到科学家自身科研能力等因素的影响,地理距离和科学家之间的联系呈现负相关关系,地理邻近性的影响仍然存在,社会邻近性和制度邻近性均对知识网络的形成有促进作用。

The spatial structure characteristics and influencing factors of knowledge networks are heated research topics in the field of economic geography.Previous studies in knowledge networks have focused on industrial cases,especially on knowledge networks at the national and city levels,while the research of individuals has been relatively limited.We firstly selected highly cited Chinese scientists based on 2014-2015 global highly cited scientists as the original data,and then established knowledge network based on the co-authorship of papers among those scientists,and finally applied social network analysis methods to examine the spatial structure of the knowledge network and used the negative binomial regression model to explore the influence mechanism of knowledge network from the perspectives of geographic proximity,social proximity and institutional proximity.The study found that:(1)the knowledge network of highly cited Chinese scientists has core-peripheral structure with the characteristics of a small-world network.(2)The spatial distribution of this knowledge network is dispersal at global scale and agglomerated at local level.(3)The formation of the knowledge network is influenced by the personal characters of those scientists.Geographical distance has a negative effect on the connection between scientists.The influence of geographic proximity still exists.Both social proximity and institutional proximity have significant positive effects on the formation of knowledge networks of highly cited Chinese scientists.