Scientific discovery and topological transitions in collaboration networks

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.     

The continuity and citation impact of scientific collaboration with different gender composition

Scientific collaboration has become an important approach for knowledge production and innovation and has received wide attention. Although gender, a demographic characteristic of scientists, has been found to influence scientific collaboration, little research has associated gender with continuous collaboration. In the current study, we classified collaboration pairs by the genders of the two collaborators and explored the relationships among gender composition, collaboration continuity, and citation impact using regression analyses. Female scholars were found to limit continuity for the collaboration pair. The results also showed that inter-gender collaborations were less continuous than intra-gender collaborations after considering the gender difference in individual persistence. In addition, we showed that the relationship between continuity and citation impact was significantly positive, and was stronger if the collaboration pairs included female scholars. This study provides a deeper understanding of gender-related scientific collaboration. It also provides continuity-related suggestions for researchers in inter-gender collaborations.     

CitNetExplorer: A new software tool for analyzing and visualizing citation networks

We present CitNetExplorer, a new software tool for analyzing and visualizing citation networks of scientific publications. CitNetExplorer can for instance be used to study the development of a research field, to delineate the literature on a research topic, and to support literature reviewing. We first introduce the main concepts that need to be understood when working with CitNetExplorer. We then demonstrate CitNetExplorer by using the tool to analyze the scientometric literature and the literature on community detection in networks. Finally, we discuss some technical details on the construction, visualization, and analysis of citation networks in CitNetExplorer.     

PageRank variants in the evaluation of citation networks

This paper explores a possible approach to a research evaluation, by calculating the renown of authors of scientific papers. The evaluation is based on the citation analysis and its results should be close to a human viewpoint. The PageRank algorithm and its modifications were used for the evaluation of various types of citation networks. Our main research question was whether better evaluation results were based directly on an author network or on a publication network. Other issues concerned, for example, the determination of weights in the author network and the distribution of publication scores among their authors. The citation networks were extracted from the computer science domain in the ISI Web of Science database. The influence of self-citations was also explored. To find the best network for a research evaluation, the outputs of PageRank were compared with lists of prestigious awards in computer science such as the Turing and Codd award, ISI Highly Cited and ACM Fellows. Our experiments proved that the best ranking of authors was obtained by using a publication citation network from which self-citations were eliminated, and by distributing the same proportional parts of the publications’ values to their authors. The ranking can be used as a criterion for the financial support of research teams, for identifying leaders of such teams, etc.     

Analysis of reference and citation copying in evolving bibliographic networks

Extensive literature demonstrates how the copying of references (links) can lead to the emergence of various structural properties (e.g., power-law degree distribution and bipartite cores) in bibliographic and other similar directed networks. However, it is also well known that the copying process is incapable of mimicking the number of directed triangles in such networks; neither does it have the power to explain the obsolescence of older papers. In this paper, we propose RefOrCite, a new model that allows for copying of both the references from (i.e., out-neighbors of) as well as the citations to (i.e., in-neighbors of) an existing node. In contrast, the standard copying model (CP) only copies references. While retaining its spirit, RefOrCite differs from the Forest Fire (FF) model in ways that makes RefOrCite amenable to mean-field analysis for degree distribution, triangle count, and densification. Empirically, RefOrCite gives the best overall agreement with observed degree distribution, triangle count, diameter, h-index, and the growth of citations to newer papers.     

Exploring all-author tripartite citation networks: A case study of gene editing

Constructing academic networks to explore intellectual structure realize academic community detection, which can promote scientific research innovation and discipline progress, constitutes an important research topic. In this study, tripartite citation is fused with co-citation and coupling relations as a way of weighting the strength of direct citations, and all-author tripartite citation networks were constructed due to the contributions of all authors to the resulting publications. For purpose of exploring the potential of the all-author exclusive and inclusive tripartite citation networks, gene editing is taken as a case study. The extensive experimental comparisons are conducted with the traditional author single-citation networks and first-author tripartite citation network in terms of network structure characteristics, identifying core scholars, and exploring intellectual structures. The following conclusions can be drawn as follows: our all-author tripartite citation networks are able to help identify the most influential scholars in the field of gene editing, and the intellectual structures from exclusive tripartite citation networks are optimal.     

The landmark citation method: analysis of a citation pattern as a collection assessment method.

The landmark citation method is a new collection assessment method based on the citation record of a single landmark article. This citation record is developed by identifying sources which cite the landmark article. A bibliography, extracted from the citation record, is then used to complete an assessment of the collection. This method was developed and used to assess the biotechnology collection of the National Library of Medicine. The information gained from this study, in addition to demonstrating the technique, also provided insight into the evolution of the biotechnology literature.     

A business citation analysis: A local follow-up study

While there is no official style for business writing, the most common citation style in business research has not been determined previously. The purpose of this study is to evaluate the top scholarly business journals to determine the most commonly used citation style in business academic research. The author used the list of 452 top business journals included in the Social Sciences Citation Index (SSCI) Journal Citation Report. The results show that 69% of business journals use a publisher-dictated style, whereas of the “traditional” citation styles, 11% use the American Psychological Association style, 10% use Harvard style, 8% use Chicago style, and none use Modern Language Association style.     

药物基因组学科研合作网络的统计学性质

药物基因组学是一门年轻的学科领域。该领域内相关科学研究工作者之间形成的科研合作关系网络,也具有类似许多大型合作关系网络数据库所具有的无尺度网络特性,其非连通合作网络内部具有较大连通组群的聚类特性和小世界特征等相关性质。     

Mining diversity subgraph in multidisciplinary scientific collaboration networks: A meso perspective

This paper proposes a framework to analyze the interdisciplinary collaboration in a coauthorship network from a meso perspective using topic modeling: (1) a customized topic model is developed to capture and formalize the interdisciplinary feature; and (2) the two algorithms Diversity Subgraph Extraction (DSE) and Constraint-based Diversity Subgraph Extraction (CDSE) are designed and implemented to extract a meso view, i.e. a diversity subgraph of the interdisciplinary collaboration. The proposed framework is demonstrated using a coauthorship network in the field of computer science. A comparison between DSE and Breadth First Search (BSF)-based subgraph extraction favors DSE in capturing the diversity in interdisciplinary collaboration. Potential possibilities for studying various research topics based on the proposed framework of analysis are discussed.     

Beyond citation analysis: a model for assessment of research impact

Question:

Is there a means of assessing research impact beyond citation analysis?

Setting:

The case study took place at the Washington University School of Medicine Becker Medical Library.

Method:

This case study analyzed the research study process to identify indicators beyond citation count that demonstrate research impact.

Main Results:

The authors discovered a number of indicators that can be documented for assessment of research impact, as well as resources to locate evidence of impact. As a result of the project, the authors developed a model for assessment of research impact, the Becker Medical Library Model for Assessment of Research.

Conclusion:

Assessment of research impact using traditional citation analysis alone is not a sufficient tool for assessing the impact of research findings, and it is not predictive of subsequent clinical applications resulting in meaningful health outcomes. The Becker Model can be used by both researchers and librarians to document research impact to supplement citation analysis.     

引文分析在图书馆期刊馆藏资源建设中的作用 --济南大学应用化学专业硕士论文引文分析研究

论文时济南大学应用化学专业2001～2004硕士研究生学位论文引文的数量、语种、类型、年代及该专业的文献半衰期进行了统计分析，时引文量最大的外文期刊进行排序并考察其在本校的收藏情况，从而掌握本校的期刊保障率，为馆藏期刊资源建设提供了参考依据。     

Collaboration prediction based on multilayer all-author tripartite citation networks: A case study of gene editing

Academic collaboration prediction is considered to be an important way to help scholars expand their research horizons and explore a vast and suitable range of partners. However, existing studies mainly rely on historical collaborations for future predictions, which has limitations in digging into credible collaboration possibilities in a wide range of cross-disciplinary contexts. In view of this, this study tries to combine three typical citation relationships (including direct citation, co-citation, and coupling) to predict prospective collaborations based on citation information that reflects the characteristics of scholars’ knowledge structure and research habits, which is supposed to provide supplement and extension for traditional implementation. To this end, we construct all-author tripartite citation networks based on the bibliographic data in the field of gene editing, and apply the Node2vec and Multi-node2vec algorithms to predict collaborations between authors in both single and multiple layers. According to compare with that of link prediction indicators (including CN, AA, PA and RA, etc.) commonly used for traditional collaboration networks, it is found that the prediction results in the multilayer all-author tripartite citation network should be relatively more accurate. The results will be helpful for scholars in the field of gene editing to explore potential collaborators with an implicit research connection.     

Non-linearity between referencing behavior and citation impact: A large-scale,discipline-level analysis

References formulate the foundation and endorsements of scientific research. Using articles published in 2005 covered by Microsoft Academic Graph, the current paper defines and calculates five indicators of references, i.e., the number of references, the number of citations of references, the age of references, the number of nodes in a reference cascade (a multi-generation reference network), and the density of bibliographic coupling networks by references, and investigates their relations with the citation impact of the focal publication. A non-linear relationship is shown in all the five indicators; specifically, we observe two types of patterns, namely inverted-L and -U relations, both presenting the existence of critical points. We further explore the discipline-level differences of such a relationship and how it relates to the characteristics of the discipline itself. Among all five indicators, the effect of disciplinary academic “environments” is universally identified. We believe that the current paper provides insightful views to the discussion regarding the significance of a reference list.     

学术性期刊与技术性期刊引文的对比分析——以《建筑结构学报》与《建筑技术》为例

以<建筑结构学报与<建筑技术引文统计为例,对学术性期刊和技术性期刊参考文献引用和著录的某些特征差异进行对比分析,简要阐述其差异的内在原因.认为在论文稿件鉴审、编辑和期刊质量评价时,对学术性期刊与技术性期刊引文的客观差异应予区别对待.     

The distribution of references across texts: Some implications for citation analysis

In citation network analysis, complex behavior is reduced to a simple edge, namely, node A cites node B. The implicit assumption is that A is giving credit to, or acknowledging, B. It is also the case that the contributions of all citations are treated equally, even though some citations appear multiply in a text and others appear only once. In this study, we apply text-mining algorithms to a relatively large dataset (866 information science articles containing 32,496 bibliographic references) to demonstrate the differential contributions made by references. We (1) look at the placement of citations across the different sections of a journal article, and (2) identify highly cited works using two different counting methods (CountOne and CountX). We find that (1) the most highly cited works appear in the Introduction and Literature Review sections of citing papers, and (2) the citation rankings produced by CountOne and CountX differ. That is to say, counting the number of times a bibliographic reference is cited in a paper rather than treating all references the same no matter how many times they are invoked in the citing article reveals the differential contributions made by the cited works to the citing paper.