以科研论文为媒介的知识合作网络已成为知识溢出的重要通道,但目前学术界对全球科研合作网络结构的复杂性涌现机制缺乏深入的探讨。基于2014年Web of Science核心合集所收录的科研论文合著数据,借助大数据挖掘技术、复杂网络、空间统计和重力模型分析,刻画了全球科研论文合作网络的拓扑结构、空间格局及其邻近性机理。结果发现：① 拓扑结构上,形成了以美国为核心的层级网络,具有小世界性和等级层次性,发育出典型的等级“核心—边缘”结构。② 空间格局上,以美国、西欧、中国和澳大利亚为顶点的“四边形”成为全球科研论文合作网络的骨架;三大中心性指标值的空间分异明显,强度中心性形成以美国为极核,加拿大、澳大利亚、中国及西欧诸国为次中心的“一超多强”格局,与之类似的介数中心性呈现北美、西欧和东亚“三足鼎立”的形态,度中心性分布则相对均匀,表现出“大分散、小集中”的“多中心—边缘集散”格局。③ 重力回归分析发现,地理距离抑制了国际科研论文合作,不过其影响力较弱;社会与经济邻近性对全球科研论文合作具有明显的促进作用,语言差异不是国际科研合作交流的障碍。

Despite increasing importance of academic papers in global knowledge flows, the structural disparities and proximity mechanism related to international scientific collaboration network attracted little attention. To fill this gap, based on data mining from Thomson Reuters' Web of Science database in 2014, its heterogeneities in topology and space were portrayed using visualizing tools such as Pajek, Gephi, VOSviewer, and ArcGIS. Topologically, 211 countries and 9928 ties are involved in global scientific collaboration network, but the international network of co-authored relations is mono-centricand dominated by the United States. It exhibits some features of a "small-world" network with the smaller average path length of 1.56 and the extremely large cluster coefficient of 0.73 compared to its counterpart, as well as the better-fitting exponential distribution accumulative nodal degree. In addition, the entire network presents a core-periphery structure with hierarchies, which is composed of 13 core countries and the periphery of 198 countries. Spatially, densely-tied and high-output areas are mainly distributed in four regions: West Europe, North America, East Asia and Australia. Moreover, the spatial heterogeneity is also observed in the distributions of three centralities. Amongst these, the countries with greater strength centrality are mainly concentrated in North America (i.e. the US and Canada), Western Europe (i.e. the UK, France, Germany, Italy and Spain), and China, noticeably in the US, which forms the polarizing pattern with one superpower of the US and great powers such as China and the UK. Similarly, the big three regions consisting of West Europe, North America and Asian-Pacific region have the peak betweenness centrality as well. Slightly different from the two above, the distribution of nodal degree centrality is uneven in the world, although regional agglomeration of high-degree countries is still observed. Last but not least, the proximity factors of its structural inequalities were also verified by correlational analysis, negative binomial regression approach and gravity model of STATA. The findings further confirm that geographical distance has weakened cross-country scientific collaboration. Meanwhile, socio-economic proximity has a positive impact on cross-country scientific collaboration, while language proximity plays a negative role.

高质量科学家的流动代表了科学知识的传播，基于高质量科学家的流动刻画近代世界科学活动中心的转移规律，对于国家制定科技战略，推动科技进步具有重要意义。该研究基于Scopus数据库1921-2020年发表的论文数据，提取高质量科学家的跨国流动序列，从而对近百年来世界科学活动中心的转移进行分析，并从学科层次研究科学活动中心的转移规律。研究结果显示：（1）科学活动中心与学科活动中心具有不唯一性，且随时间呈现多中心化，美国、英国一直占据科学活动中心位置，其次为德、意等发达国家，是多个阶段的世界科学活动中心与学科活动中心；（2）科学活动中心与学科活动中心具有转移性，且转移方向不是单向的，但二者的演化具有一致性，即科学活动中心可视为不同学科活动中心的堆叠效应；（3）不同时期不同学科对于科学活动中心形成的贡献度不同，随着科学多元化与学科交叉融合，这种贡献差异性降低；（4）中国自2004年成为世界科学活动中心之一，但与发达国家相比仍有较大差距，需进一步加大科研投入力度，促进学科平衡发展。

The concept of “world scientific activity center” was proposed by J. D. Bernal in the year of 1957, and have raised many interests from globle researchers. Study the matastasis rule of world scientific activity center is of importance to the policy makers for establishing the R&D development strategies. Most of the previous studies analyzed the matastasis rule of the world scientific activity center based on the researchers’ achievements. However, this method is not suitable at present under the background of global integration, while the collaboration among researchers increasing greatly. The transnational flows of high-quality scientists was regarded as can be the representive of vital knowledge spreading. Previous researches have validated this based on study the matastasis of Nobel prize winners or the authors of top journals. They contributed to understand the related rule of world scientific activity center at present. However, these studies also have some limitations. Such as they only studied a small group of researchers, thus the whole phenomenon of the scientists transfer could not be reflected. Based on the above analysis, this paper collects the scientific papers published from 1921 to 2020 in the Scopus database, extracts the transnational flow sequence of each high-quality scientists, which are the top1% h-index researchers in each disciplines of the Scopus database, from these papers, and systematically analyzes the matastasis rule of world scientific activity center in the 100 years both in the whole level and the disciplinary level. Specially, the ten important disciplines including agricultural and biological sciences, biochemistry, genetics and molecular biolog, physics and astronomy, multidisciplinary, neuroscience, immunology and microbiology, materials science, chemistry, medicine, and engineering are selected into study, due to their intimate relationships with the world scientific activity center proven by previous studies. Results show that, first, the world scientific center or disciplinary activity center is not sole. There could be more than one world scientific center or disciplinary activity center in the same period. For example, the USA, UK, Germany and Italy have been the world scientific activity centers in multible periods and among various disciplines. Second, both the world scientific activity center and the disciplinary activity center could transfer over time, and the transfer direction was not one-way. Besides, the transfer process of these two kind of centers are synchronous. When a region was the world scientific activity center, it was often several disciplines’ activity center, and vice versa. For example, the USA was almost all the disciplines’ activity centers in the entire period. Thus the world scientific activity center could be regarded as the additive effect of the different disciplines. Third, different disciplines contributed differently to the formation of scientific activity center in the certain period. The diversified development of science and the interdisciplinary integration have moderated the difference, it is hard to distinguish which disciplines have the higher contribution degrees. Last, China has been the world scientifc activity center since the year of 2004. But it still has a significant gap from the developed countries. The disciplines of multidisciplinary, medicine and neuroscience still need to be developed in the future. Specially, significant attentions should be paid to the emerged scientific and technological domains, the R&D input should be raised and the balance development among disciplines should be also sidelined in the future.

中国崛起,关键在于科技崛起。在当前技术针对与封锁的国际环境中,探讨建构以中国为核心的全球创新网络和科学制定中国未来科技战略是当前创新地理学和地缘政治学交叉之下研究的重点课题,而明晰全球地缘科技格局及其演变过程则是基础所在。本文基于2001—2015年全球国家（地区）间的知识产权进出口数据,在研究全球知识产权贸易格局和网络结构的基础上,探讨了全球地缘科技体系的时空演化特征,得出以下结论：① 全球知识产权贸易网络两极分化显著,是一典型的小世界网络,以美国为核心的金字塔结构不断夯实;② 基于敏感性和脆弱性模型阐释的全球知识产权贸易的非对称依赖性进一步验证了美国是全球地缘科技格局的核心,且其核心地位不断巩固和加强。

加强与“一带一路”国家科技合作是当前政府和学术界高度关注的问题。在美国专利商标局（USTPO）和Web of Science数据库检索中国和29个“一带一路”沿线国家的合作专利和论文，分别对国家分布、时序分布、主要申请人（机构）和主要技术领域（方向）等现状进行分析。结果显示：①科技合作总体上保持增长趋势，可分成起步期、快速增长期和稳定增长期三个阶段；②知识创新合作比技术创新合作更活跃，合作论文数量是合作专利的9倍以上；③合作区域呈现不均衡的特征，前五位国家的合作专利和论文数量分别占总数的82.1%和53.2%；④合作专利的申请人和合作论文中方机构的集中度均比较高，专利申请人以企业为主体；⑤合作的技术领域和方向比较聚焦，合作专利集中在数字数据处理、半导体器件、无线通信网络等领域，合作论文集中在物理、工程、化学等方向。研究结论可以为未来进一步开展科技合作和政策制定提供借鉴。

The extent to which scientific advances support marketplace inventions is largely unknown. We study 4.8 million U.S. patents and 32 million research articles to determine the minimum citation distance between patented inventions and prior scientific advances. We find that most cited research articles (80%) link forward to a future patent. Similarly, most patents (61%) link backward to a prior research article. Linked papers and patents typically stand 2 to 4 degrees distant from the other domain. Yet, advances directly along the patent-paper boundary are notably more impactful within their own domains. The distance metric further provides a typology of the fields, institutions, and individuals involved in science-to-technology linkages. Overall, the findings are consistent with theories that emphasize substantial and fruitful connections between patenting and prior scientific inquiry.Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

［目的/意义］识别专利丛林是专利风险识别的基础性工作之一。文章从产业链视角出发，利用社会网络分析技术识别特定产业的专利丛林,对企业构建完善的知识产权保护体系、实现自由经营具有重要意义。［方法/过程］基于LDA模型对技术领域专利信息进行主题划分，运用关联分析对主题与产业技术链进行映射，通过社会网络分析方法对产业链的专利丛林进行测量与分析。［结果/结论］以美国焊接机器人领域的专利为数据源，识别了产业链上的专利丛林。结合专利风险特点与分析结果，提出了相应的对策与建议。

This paper explores the complex relationship between scientific novelty and technological impact. We measure novel science as publications which make new combinations of prior knowledge, as reflected in new combinations of journals in their references, and trace links between science and technology by scientific references in patent applications. We draw on all the Web of Science SCIE journal articles published in 2001 and all the patents in PATSTAT (October 2013 edition). We find that the small proportion of scientific publications which score on novelty, particularly the 1% highly novel scientific publications in their field, are significantly and sizably more likely to have direct technological impact than comparable non-novel publications. In addition to this superior likelihood of direct impact, novel science also has a higher probability for indirect technological impact, being more likely to be cited by other scientific publications which have technological impact. Among the set of scientific publications cited at least once by patents, there are no additional significant differences in the speed or the intensity of the technological impact between novel and non-novel scientific prior art, but the technological impact from novel science is significantly broader and reaching new technology fields previously not impacted by its scientific discipline. Novel science is also more likely to lead to patents which are themselves novel.