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1.
We analyze the advent and development of eight scientific fields from their inception to maturity and map the evolution of their networks of collaboration over time, measured in terms of co-authorship of scientific papers. We show that as a field develops it undergoes a topological transition in its collaboration structure between a small disconnected graph to a much larger network where a giant connected component of collaboration appears. As a result, the number of edges and nodes in the largest component undergoes a transition between a small fraction of the total to a majority of all occurrences. These results relate to many qualitative observations of the evolution of technology and discussions of the “structure of scientific revolutions”. We analyze this qualitative change in network topology in terms of several quantitative graph theoretical measures, such as density, diameter, and relative size of the network's largest component.To analyze examples of scientific discovery we built databases of scientific publications based on keyword and citation searches, for eight fields, spanning experimental and theoretical science, across areas as diverse as physics, biomedical sciences, and materials science. Each of the databases was vetted by field experts and is the result of a bibliometric search constructed to maximize coverage, while minimizing the occurrence of spurious records. In this way we built databases of publications and authors for superstring theory, cosmic strings and other topological defects, cosmological inflation, carbon nanotubes, quantum computing and computation, prions and scrapie, and H5N1 influenza. We also built a database for a classical example of “pathological” science, namely cold fusion. All these fields also vary in size and in their temporal patterns of development, with some showing explosive growth from an original identifiable discovery (e.g. carbon nanotubes) while others are characterized by a slow process of development (e.g. quantum computers and computation).We show that regardless of the detailed nature of their developmental paths, the process of scientific discovery and the rearrangement of the collaboration structure of emergent fields is characterized by a number of universal features, suggesting that the process of discovery and initial formation of a scientific field, characterized by the moments of discovery, invention and subsequent transition into “normal science” may be understood in general terms, as a process of cognitive and social unification out of many initially separate efforts. Pathological fields, seemingly, never undergo this transition, despite hundreds of publications and the involvement of many authors. 相似文献
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作者共现网络的科学研究结构揭示能力比较研究 总被引：1，自引：0，他引：1
作者共现网络在科学研究领域结构分析中具有非常重要的作用,本文构建了作者合作、作者共被引、作者文献耦合、作者关键词耦合及作者期刊耦合五种网络,利用层次聚类和网络关联分析比较不同共现网络揭示科学研究结构的能力。通过层次聚类发现：作者文献耦合网络的准确性和精确性最高,作者共被引网络和作者合作网络其次,作者关键词耦合网络的结果容易受到干扰,作者期刊耦合网络的分析效果较差。通过网络关联分析发现：作者合作网络与其他网络的相关性都相对较低,与其他网络发现的角度不同;作者文献耦合网络与其他几种网络之间的相关性最高,对其他网络分析结果的替代性较强,多种方法结合运用更能反映科学研究的实际结构。本文还讨论了共现网络子结构研究中凝聚子群分析及中心性指标的适用性问题。图5。表4。参考文献16。 相似文献
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《Journal of Informetrics》2022,16(2):101280
International mobility in academia can enhance the human and social capital of researchers and consequently their scientific outcome. However, there is still a very limited understanding of the different mobility patterns among scholars with various socio-demographic characteristics. By studying these differences, we can detect inequalities in access to scholarly networks across borders, which can cause disparities in scientific advancement. The aim of this study is twofold. First, we investigate to what extent individuals’ factors (e.g., country, career stage, and field of research) associate with the mobility of male and female researchers. Second, we explore the relationship between mobility and scientific activity and impact. For this purpose, we used a bibliometric approach to track the mobility of authors. To compare the researchers’ scientific outcomes, we considered the number of publications and received citations as indicators, as well as the number of unique co-authors in all their publications. We also analyzed the co-authorship network of researchers and compared centrality measures of “mobile” and “non-mobile” researchers. Results show that researchers from North America and Sub-Saharan Africa, particularly female ones, have the lowest, respectively, highest tendency towards international mobility. Having international co-authors increases the probability of international movement. Our findings uncover gender inequality in international mobility across scientific fields and countries. Across genders, researchers in the Physical sciences have the most and in the Social sciences the least rate of mobility. We observed more mobility for Social scientists at the advanced career stage, while researchers in other fields prefer to move at earlier career stages. Also, we found a positive correlation between mobility and scientific outcomes, but no apparent difference between females and males. Indeed, researchers who have started mobility at the advanced career stages had a better scientific outcome. Comparing the centrality of mobile and non-mobile researchers in the co-authorship networks reveals a higher social capital advantage for mobile researchers. 相似文献
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将复杂网络的研究方法引入到科研合作网络的研究中,为分析和评价科研人员提供了一个新途径.文章以合作网络为背景,微观深入地研究了科研合作网络中个体成员的网络生命特性,从全局网络和局部社团演化的角度定量分析个体网络生命过程对网络发展的影响.文章以大量的科技文献数据为实验数据集,以网络演化为线索跟踪个体成员的生命过程,同时考虑网络演化中的普通成员和核心成员对社团演化的不同影响,定量分析演化特性和个体网络生命过程.数据分析证实了科研团队要持续不断地发展,既要不断吸纳新成员为科研团队注入新活力,同时又要有相对稳定的中坚力量维持着团队的科研方向.更进一步地,文章的研究方法可以扩展到对其他社会组织分析,追踪分析相关组织的发展趋势及关键人物对组织演化的影响. 相似文献
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文章简要介绍了复杂网络的概念和科研合作网络相关知识,对生命科学领域国内561万多篇期刊论文进行了统计与合作网络分析,并从合作网络中抽取出科研机构子网络和医院子网络,针对复杂网络的几个特征进行对比性分析,找出了各个网络的不同特性,分析说明不同机构的科研合作模式。 相似文献
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《Journal of Informetrics》2019,13(2):708-716
Peer review is not only a quality screening mechanism for scholarly journals. It also connects authors and referees either directly or indirectly. This means that their positions in the network structure of the community could influence the process, while peer review could in turn influence subsequent networking and collaboration. This paper aims to map these complex network implications by looking at 2232 author/referee couples in an interdisciplinary journal that uses double blind peer review. By reconstructing temporal co-authorship networks, we found that referees tended to recommend more positively submissions by authors who were within three steps in their collaboration network. We also found that co-authorship network positions changed after peer review, with the distances between network neighbours decreasing more rapidly than could have been expected had the changes been random. This suggests that peer review could not only reflect but also create and accelerate scientific collaboration. 相似文献
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We develop and propose a new counting method at the aggregate level for contributions to scientific publications called modified fractional counting (MFC). We show that, compared to traditional complete-normalized fractional counting, it eliminates the extreme differences in contributions over time that otherwise occur between scientists that mainly publish alone or in small groups and those that publish with large groups of co-authors. As an extra benefit we find that scientists in different areas of research turn out to have comparable average contributions to scientific articles. We test the method on scientists at Norway’s largest universities and find that, at an aggregate level, it indeed supports comparability across different co-authorship practices as well as between areas of research. MFC is thereby useful whenever the research output from institutions with different research profiles are compared, as e.g., in the Leiden Ranking. Finally, as MFC is actually a family of indicators, depending on a sensitivity parameter, it can be adapted to the circumstances. 相似文献
10.
Although structuration theory (ST) has endured a considerable influence in communication research across various domains, there remains a paucity of quantitative empirical research using ST as a viable framework. The purpose of this article is to develop an adapted structurational framework to explain the emergence of communication networks. The adapted framework distinguishes between relational states/events and internal/external structural rules. For analysis, we introduce multipanel relational event modeling, a technique using processual inference that can empirically demonstrate the recursive nature of system and structure. As an introductory example of both the framework and method, we examined communication, using cell-phone data, of students living in the same dormitory from September 2008 through February 2009. Our results demonstrated how different structures (i.e., perceived social relations and internal/external structural rules) are reproduced and transformed over time. Our research has implications for communication research dealing with recursivity, event-driven network analysis, the changing nature of the phone call, and the promise of computational communication science. 相似文献
11.
选择8种国内竞争情报领域核心期刊1986～2010年刊载的合著论文为样本,构建我国竞争情报领域的合著网络。通过网络特征分析、聚类子群分析、核心—边缘分析、中心度分析等社会网络分析方法研究竞争情报合著网络的整体结构特征、核心作者群、小团体现象以及资源的分布情况。研究结果表明,竞争情报领域的合著网络信息畅通,联系疏散,资源聚集度高,大部分高产作者的合作研究十分有限。在科研合作和作者评价研究上,社会网络分析和信息计量方法具有良好的互补性。 相似文献
12.
Dalibor Fiala 《Journal of Informetrics》2012,6(3):370-388
In the past, recursive algorithms, such as PageRank originally conceived for the Web, have been successfully used to rank nodes in the citation networks of papers, authors, or journals. They have proved to determine prestige and not popularity, unlike citation counts. However, bibliographic networks, in contrast to the Web, have some specific features that enable the assigning of different weights to citations, thus adding more information to the process of finding prominence. For example, a citation between two authors may be weighed according to whether and when those two authors collaborated with each other, which is information that can be found in the co-authorship network. In this study, we define a couple of PageRank modifications that weigh citations between authors differently based on the information from the co-authorship graph. In addition, we put emphasis on the time of publications and citations. We test our algorithms on the Web of Science data of computer science journal articles and determine the most prominent computer scientists in the 10-year period of 1996–2005. Besides a correlation analysis, we also compare our rankings to the lists of ACM A. M. Turing Award and ACM SIGMOD E. F. Codd Innovations Award winners and find the new time-aware methods to outperform standard PageRank and its time-unaware weighted variants. 相似文献
13.
《Journal of Informetrics》2023,17(1):101372
Based on complementarity in terms of factors such as skill and knowledge, researchers might build long-term partnerships with one another during their scientific careers. It has been shown that such relationships have a significant positive impact on researchers’ scientific performance. However, the preferential connection mechanism in collaboration networks actually suggests the unequal positions of participants in the process of scientific collaboration. This study argues that this phenomenon is very similar to the symbiosis function in the natural world. Hence, this work provides a novel interpretation of scientific collaboration patterns from the perspective of symbiosis. In more detail, long-term collaboration relationships are investigated based on the scope of an academician dataset with multiple fields and an economic dataset. With the aid of a quantitative metric for symbiosis degree, six meta-patterns of the short-term evolution of symbiosis degree are proposed. Furthermore, by exploring the evolution of meta-patterns, four scientific collaboration patterns are summarized according to the common characteristics as follows: leading growth, continuous leadership, chasing each other, and standing on equal footing. Extensive experimental results on an academician dataset with multiple fields show that the collaboration network evolution of four collaboration patterns is consistent with our summarized characteristics based on symbiosis. This indicates that our symbiosis-based framework can be used to effectively interpret the developmental and evolutionary trajectories of scientific collaboration. 相似文献
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In this paper, we develop a novel methodology within the IDCP measuring framework for comparing normalization procedures based on different classification systems of articles into scientific disciplines. Firstly, we discuss the properties of two rankings, based on a graphical and a numerical approach, for the comparison of any pair of normalization procedures using a single classification system for evaluation purposes. Secondly, when the normalization procedures are based on two different classification systems, we introduce two new rankings following the graphical and the numerical approaches. Each ranking is based on a double test that assesses the two normalization procedures in terms of the two classification systems on which they depend. Thirdly, we also compare the two normalization procedures using a third, independent classification system for evaluation purposes. In the empirical part of the paper we use: (i) a classification system consisting of 219 sub-fields identified with the Web of Science subject-categories; an aggregate classification system consisting of 19 broad fields, as well as a systematic and a random assignment of articles to sub-fields with the aim of maximizing or minimizing differences across sub-fields; (ii) four normalization procedures that use the field or sub-field mean citations of the above four classification systems as normalization factors; and (iii) a large dataset, indexed by Thomson Reuters, in which 4.4 million articles published in 1998–2003 with a five-year citation window are assigned to sub-fields using a fractional approach. The substantive results concerning the comparison of the four normalization procedures indicate that the methodology can be useful in practice. 相似文献
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Chaomei Chen Yue Chen Mark Horowitz Haiyan Hou Zeyuan Liu Donald Pellegrino 《Journal of Informetrics》2009,3(3):191-209
We propose an explanatory and computational theory of transformative discoveries in science. The theory is derived from a recurring theme found in a diverse range of scientific change, scientific discovery, and knowledge diffusion theories in philosophy of science, sociology of science, social network analysis, and information science. The theory extends the concept of structural holes from social networks to a broader range of associative networks found in science studies, especially including networks that reflect underlying intellectual structures such as co-citation networks and collaboration networks. The central premise is that connecting otherwise disparate patches of knowledge is a valuable mechanism of creative thinking in general and transformative scientific discovery in particular. In addition, the premise consistently explains the value of connecting people from different disciplinary specialties. The theory not only explains the nature of transformative discoveries in terms of the brokerage mechanism but also characterizes the subsequent diffusion process as optimal information foraging in a problem space. Complementary to epidemiological models of diffusion, foraging-based conceptualizations offer a unified framework for arriving at insightful discoveries and optimizing subsequent pathways of search in a problem space. Structural and temporal properties of potentially high-impact scientific discoveries are derived from the theory to characterize the emergence and evolution of intellectual networks of a field. Two Nobel Prize winning discoveries, the discovery of Helicobacter pylori and gene targeting techniques, and a discovery in string theory demonstrated such properties. Connections to and differences from existing approaches are discussed. The primary value of the theory is that it provides not only a computational model of intellectual growth, but also concrete and constructive explanations of where one may find insightful inspirations for transformative scientific discoveries. 相似文献
17.
Convexity in a network (graph) has been recently defined as a property of each of its subgraphs to include all shortest paths between the nodes of that subgraph. It can be measured on the scale [0, 1] with 1 being assigned to fully convex networks. The largest convex component of a graph that emerges after the removal of the least number of edges is called a convex skeleton. It is basically a tree of cliques, which has been shown to have many interesting features. In this article the notions of convexity and convex skeletons in the context of scientific collaboration networks are discussed. More specifically, we analyze the co-authorship networks of Slovenian researchers in computer science, physics, sociology, mathematics, and economics and extract convex skeletons from them. We then compare these convex skeletons with the residual graphs (remainders) in terms of collaboration frequency distributions by various parameters such as the publication year and type, co-authors’ birth year, status, gender, discipline, etc. We also show the top-ranked scientists by four basic centrality measures as calculated on the original networks and their skeletons and conclude that convex skeletons may help detect influential scholars that are hardly identifiable in the original collaboration network. As their inherent feature, convex skeletons retain the properties of collaboration networks. These include high-level structural properties but also the fact that the same authors are highlighted by centrality measures. Moreover, the most important ties and thus the most important collaborations are retained in the skeletons. 相似文献
18.
基金视角下的学科知识流动网络构建与分析 总被引：1，自引：0，他引：1
[目的/意义] 在学科交叉融合的背景和趋势下,科研人员的跨学科研究行为促进了知识在不同学科之间的共享与流动。以基金领域为视角,研究学科知识流动,以期为基金管理工作提出建议。[方法/过程] 提出基于基金代码共现的学科知识流动强度测量方法,并利用社会网络分析方法,对193517个国家自然科学基金项目数据构建学科知识流动网络,探究网络的演变过程以及不同学科层次内知识流动路径。[结果/结论] 通过以上分析,得到如下结论:学科知识流动网络是无标度网络,随着时间的推移,网络的规模和结构都发生显著的变化,网络中重要节点呈非稳态;不同学部之间,存在若干条较为重要的知识流动路径;在某一个学部内,具有较广影响力的一类学科往往更容易构成知识流动链条。 相似文献
19.
In this contribution, we develop a new approach to explore the process of knowledge transition from discovery-oriented science to technological fields, via applications-oriented research, including a mediator set. This trajectory is referred to as the D-A-T trajectory. It is shown how it can be constructed and measures are proposed to characterize the relational strength among different environments (discovery oriented research, applications-oriented research and patents) and the speed of evolution. Our approach is illustrated by a case study of three fundamental restriction enzymes articles. Among other results we found that 387 patents cited 124 of the 988 articles (a share of 12.55%) in the mediator set. Defining the non-patent references (NPR) transition rate as the number of citing patents divided by the number of articles in the mediator set yields a value 0.392. Our results suggest that the D-A-T path acts as a backbone and reveals important “invisible contributions” of an original scientific work during its evolution from discovery oriented research to outside academia. Our contribution provides a useful tool for bridging the existing gap in detecting the transition of knowledge between science and technology. 相似文献