中美知识融合网络与知识扩散网络对比  

Knowledge Integration Network and Knowledge Diffusion Network Between China and the United States of America

作　　者：王雪莹 刘珊 陈洪侃 步一[1] Wang Xueying;Liu Shan;Chen Hongkan;Bu Yi(Department of Information Management,Peking University,Beijing 100871)

机构地区：[1]北京大学信息管理系,北京100871

出　　处：《情报杂志》2024年第5期167-175,166,共10页Journal of Intelligence

基　　金：国家自然科学基金“基于因果推断的高学术影响力跨学科团队早期识别研究”(编号:72104007);国家自然科学基金“基于多样性、关系链接和知识依赖的跨学科科研团队合作网络结构与演化研究”(编号:72174016);教育部人文社会科学研究青年基金项目“复杂网络视角下科学文献的知识融合与知识扩散对比研究”(编号:21YJC870001)研究成果。

摘　　要：[研究目的]当前借助引文关系开展知识流动规律分析的研究已经十分常见,但对于知识的融合与扩散过程的研究还不够深入。从复杂网络视角分析中美学者所创造知识的流动规律有助于厘清两地的科学生产力及知识流动的差异。[研究方法]通过引用关系构建知识融合级联网络和知识扩散级联网络,采用复杂网络分析法从网络数量特征、网络结构特征和级联网络国别等特征维度对中美知识融合网络和知识扩散网络进行对比分析。[研究结论]研究发现,纯美国学者组发表文献不论是知识融合级联网络还是知识扩散级联网络规模均更大,形成的知识融合级联网络密度、接近中心性和PageRank平均数更大。物理学相比于社会学,其文献的知识融合级联网络和知识扩散级联网络呈现更加稠密、节点联系更加紧密、中心性更强的结构。本研究有助于深化对知识融合与知识扩散的认识,加深对中美两国科研生产力差异的理解。[Research purpose]Research on knowledge flow pattern analysis via citation relationships is wildly carried out,while exploration on the integration and diffusion processes of knowledge is not sufficient enough.Analyzing the flow patterns of knowledge created by Chinese and American scholars from the perspective of complex networks can help understand the differences in scientific productivity and knowledge flow between China and the U.S.[Research method]By building reference cascade networks and citation cascade networks via using citation relationships,this study conducts a comparative analysis of Chinese and U.S.knowledge integration networks and knowledge diffusion networks in terms of network quantitative characteristics,network structural features,and cascade country characteristics.[Research conclusion]It is found that U.S.scholars published a larger cascade of literature.The knowledge integration cascade network of the U.S.category has higher density,greater proximity centrality and greater wean value of Pagernak.Compared to the sociology literature,the physics literature cascade presents a denser,more connected,and more centered structure.This research contributes to a deeper understanding of knowledge integration and diffusion,enhancing the understanding of the differences in scientific productivity between China and the U.S.

关 键 词：科学文献 引文级联网络 复杂网络 知识融合 知识扩散 科学生产力 中国 美国 

分 类 号：G353.1[文化科学—情报学]