The cognitive structure of current cardiovascular research

This paper presents a citation analysis of the cognitive structure of current cardiovascularresearch. Used methods are co-citation analysis, bibliographic coupling and quantitative analysisof title words. Tables and graphs reveal: (1) The journal co-citation structure; (2) the cognitivecontent and the bibliometric structure of clusters based on co-citation; (3) the cognitive contentand the bibliometric structure of clusters based on bibliographic coupling. A predominance ofdifferent research aspects on coronary artery disease was found in clusters based on co-citations aswell as in clusters based on bibliographic coupling.     

Triple Helix indicators as an emergent area of enquiry: a bibliometric perspective

This contribution explores how work on Triple Helix (TH) indicators has evolved. Over the past 15 years a body of literature has emerged that brings together a variety of approaches to capture, map or measure the dynamics of TH relationships. We apply bibliographic coupling and co-citation in combination with content analysis to develop a better understanding of this literature. We identify several clusters that can be aggregated to two broad streams of work—one ‘neo-evolutionary’, the other ‘neo-institutional’ in nature. We make this observation both for bibliographic coupling and co-citation analyses which we take as indication of an emerging differentiation of the field. Our content analysis underlines this observation about the ‘two faces’ of the TH. We conclude this paper with a discussion of future opportunities for research. We see great potential in developing the application side of TH indicators.     

Visualizing the research on pervasive and ubiquitous computing

The aim of this paper is to identify the research status quo on pervasive and ubiquitous computing via scientometric analysis. Information visualization and knowledge domain visualization techniques were adopted to determine how the study of pervasive and ubiquitous computing has evolved. A total of 5,914 papers published between 1995 and 2009 were retrieved from the Web of Science with a topic search of pervasive or ubiquitous computing. CiteSpace is a java application for analyzing and visualizing a wide range of networks from bibliographic data. By use of it, we generated the subject category network to identify the leading research fields, the research power network to find out the most productive countries and institutes, the journal co-citation map to identify the distribution of core journals, the author co-citation map to identify key scholars and their co-citation patterns, the document co-citation network to reveal the ground-breaking literature and detect the co-citation clusters on pervasive and ubiquitous computing, and depicted the hybrid network of keywords and noun phrases to explore research foci on pervasive and ubiquitous computing over the entire span 1995–2009.     

Co-citation,bibliographic coupling and a characterization of lattice citation networks

In this article we study directed, acyclic graphs. We introduce the head and tail order relations and study some of their properties. Recalling the notions of generalized bibliographic coupling and generalized co-citation, and introducing a new property, called the l - property, we come to a characterization of lattices. As document citation networks are concrete realizations of directed acyclic graphs all our results are directly applicable to citation analysis. This revised version was published online in June 2006 with corrections to the Cover Date.     

Comparative study on structure and correlation among author co-occurrence networks in bibliometrics

This paper introduces author-level bibliometric co-occurrence network by discussing its history and contribution to the analysis of scholarly communication and intellectual structure. The difference among various author co-occurrence networks, which type of network shall be adapted in different situations, as well as the relationship among these networks, however, remain not explored. Five types of author co-occurrence networks were proposed: (1) co-authorship (CA); (2) author co-citation (ACC); (3) author bibliographic coupling (ABC); (4) words-based author coupling (WAC); (5) journals-based author coupling (JAC). Networks of 98 high impact authors from 30 journals indexed by 2011 version of Journal Citation Report-SSCI under the Information Science & Library Science category are constructed for study. Social network analysis and hierarchical cluster analysis are applied to identify sub-networks with results visualized by VOSviewer software. QAP test is used to find potential correlation among networks. Cluster analysis results show that all the five types of networks have the power for revealing intellectual structure of sciences but the revealed structures are different from each other. ABC identified more sub-structures than other types of network, followed by CA and ACC. WAC result is easily affected and JAC result is ambiguous. QAP test result shows that ABC network has the highest proximity with other types of networks while CA network has relatively lower proximity with other networks. This paper will provide a better comprehension of author interaction and contribute to cognitive application of author co-occurrence network analysis.     

A relevance ranking method for citation-based search results

A growing number of researchers are exploring the use of citation relationships such as direct citation, bibliographic coupling, and co-citation for information retrieval in scientific databases and digital libraries. In this paper, I propose a method of ranking the relevance of citation-based search results to a set of key, or seed, papers by measuring the number of citation relationships they share with those key papers. I tested the method against 23 published systematic reviews and found that the method retrieved 87% of the studies included in these reviews. The relevance ranking approach identified a subset of the citation search results that comprised 27% of the total documents retrieved by the method, and 7% of the documents retrieved by these reviews, but that contained 75% of the studies included in these reviews. Additional testing suggested that the method may be less appropriate for reviews that combine literature in ways that are not reflected in the literature itself. These results suggest that this ranking method could be useful in a range of information retrieval contexts.     

Betweenness and diversity in journal citation networks as measures of interdisciplinarity—A tribute to Eugene Garfield

Journals were central to Eugene Garfield’s research interests. Among other things, journals are considered as units of analysis for bibliographic databases such as the Web of Science and Scopus. In addition to providing a basis for disciplinary classifications of journals, journal citation patterns span networks across boundaries to variable extents. Using betweenness centrality (BC) and diversity, we elaborate on the question of how to distinguish and rank journals in terms of interdisciplinarity. Interdisciplinarity, however, is difficult to operationalize in the absence of an operational definition of disciplines; the diversity of a unit of analysis is sample-dependent. BC can be considered as a measure of multi-disciplinarity. Diversity of co-citation in a citing document has been considered as an indicator of knowledge integration, but an author can also generate trans-disciplinary—that is, non-disciplined—variation by citing sources from other disciplines. Diversity in the bibliographic coupling among citing documents can analogously be considered as diffusion  or differentiation of knowledge across disciplines. Because the citation networks in the cited direction reflect both structure and variation, diversity in this direction is perhaps the best available measure of interdisciplinarity at the journal level. Furthermore, diversity is based on a summation and can therefore be decomposed; differences among (sub)sets can be tested for statistical significance. In the appendix, a general-purpose routine for measuring diversity in networks is provided.     

Similarity measures for document mapping: A comparative study on the level of an individual scientist

This paper investigates the utility of the Inclusion Index, the Jaccard Index and the Cosine Index for calculating similarities of documents, as used for mapping science and technology. It is shown that, provided that the same content is searched across various documents, the Inclusion Index generally delivers more exact results, in particular when computing the degree of similarity based on citation data. In addition, various methodologies such as co-word analysis, Subject-Action-Object (SAO) structures, bibliographic coupling, co-citation analysis, and self-citation links are compared. We find that the two former ones tend to describe rather semantic similarities that differ from knowledge flows as expressed by the citation-based methodologies.     

A comparison of two bibliometric methods for mapping of the research front

Summary This paper builds on previous research concerned with the classification and specialty mapping of research fields. Two methods are put to test in order to decide if significant differences as to mapping results of the research front of a science field occur when compared. The first method was based on document co-citation analysis where papers citing co-citation clusters were assumed to reflect the research front. The second method was bibliographic coupling where likewise citing papers were assumed to reflect the research front. The application of these methods resulted in two different types of aggregations of papers: (1) groups of papers citing clusters of co-cited works and (2) clusters of bibliographically coupled papers. The comparision of the two methods as to mapping results was pursued by matching word profiles of groups of papers citing a particular co-citation cluster with word profiles of clusters of bibliographically coupled papers. Findings suggested that the research front was portrayed in two considerably different ways by the methods applied. It was concluded that the results in this study would support a further comparative study of these methods on a more detailed and qualitative ground. The original data set encompassed 73,379 articles from the fifty most cited environmental science journals listed in Journal Citation Report, science edition downloaded from the Science Citation Index on CD-ROM.     

Using ‘core documents’ for the representation of clusters and topics

The notion of ‘core documents’, first introduced in the context of co-citation analysis and later re-introduced for bibliographic coupling, refers to the representation of the core of a publication set according to given criteria. In the present study, the notion of core documents is extended to the combination of citation-based and textual links. It is shown that core documents defined this way can be used to represent and describe document clusters and topics at different levels of aggregation. Methodology is illustrated using the example of two ISI Subject Categories selected from applied and social sciences.     

Research evolution in science parks and incubators: foundations and new trends

In this paper we undertake a quantitative review of the existing literature on parks and incubators to identify their foundations from a longitudinal perspective. To do so, we searched records in the SSCI database from 1990 to 2015 and identified 318 citing documents, which we split into four periods of 5 years each, to identify the interactions and path dependence that exist between different foundations of research. We evaluate the evolution of the theoretical foundations of this research line taking into account changes in citations over time. We also identify areas of future research closely connected with the theoretical foundations already identified. For this purpose, we used two bibliometric techniques—co-citation analysis and bibliographic coupling—that enable us to assess the thematic similarity between scientific publications based on overlaps in their referencing patterns.     

Reviewing the intellectual structure and evolution of the innovation systems approach: A social network analysis

The increased attention of policymakers and researchers to the concept of innovation systems in recent decades has led to an increase in studies in this field and, consequently, its dynamics. This increase in the number of studies indicates the necessity of conducting studies to delineate the intellectual structure and process of development and evolution of this field. The present study aims to present a picture of the structure, evolution, and dynamics of innovation systems through the analysis of academic social networks based on bibliometric criteria and identify emerging issues for research. Accordingly, using citation, word co-occurrence, co-citation, and bibliographic coupling analyses, we analyzed 3250 documents which had been published between 1988 and 2018 and extracted from the Web of Science database. Through a systematic review, theoretical roots and frameworks affecting this field were identified and the existing research streams were introduced. According to the analyses, historical and contemporary views were categorized into four clusters. In addition, the most important and emerging issues in this field were identified and the most influential documents, journals, and authors were introduced.     

Overlapping thematic structures extraction with mixed-membership stochastic blockmodel

It is increasing important to identify automatically thematic structures from massive scientific literature. The interdisciplinarity enables thematic structures without natural boundaries. In this work, the identification of thematic structures is regarded as an overlapping community detection problem from the large-scale citation-link network. A mixed-membership stochastic blockmodel, armed with stochastic variational inference algorithm, is utilized to detect the overlapping thematic structures. In the meanwhile, in order to enhance readability, each theme is labeled with soft mutual information based method by several topical terms. Extensive experimental results on the astro dataset indicate that mixed-membership stochastic blockmodel primarily uses the local information and allows for the pervasive overlaps, but it favors similar sized themes, which disqualifies this approach from being used to extract the thematic structures from scientific literature. In addition, the thematic structures from the bibliographic coupling network is similar to those from the co-citation network.     

Citation genetic genealogy: a novel insight for citation analysis in scientific literature

Citation relationships are commonly described with citation network or citation graph, but in this article, the author introduced the notion of citation genetic genealogy and apply it in citation analysis. A citing document usually only uses pieces of its cited document, so the author of this article defined these valuable pieces of a scientific document, which carry the information that have been used by its citing documents as its document genes. Besides, with the definition of symbolic information of a scientific document, the conclusion that a citing document inherited the document genes from its references can be drawn. Based on these understandings, citation genetic genealogy is constructed to describe citation relationships. With citation genetic genealogy, it is easy to map the citation relationships, like bibliographic coupling and co-citation, with familiar family relationships and illustrate the inheritance relationships in scientific literatures. Also, citation genetic genealogy may provide an interface between the citation analysis of a document set and the content analysis for each individual document inside this document set.     

Collaborative network of firms: antecedents and state-of-the-art properties

The concept of collaborative networks has attracted considerable attention, especially in two knowledge domains: innovation and operation management. Although collaborative networks have evolved into many forms, their central role in triggering debates has not gone unnoticed. In this paper, we aim to contribute to these debates through a bibliometric review of a decade of research on collaborative networks (2002–2015). By using a combination of document co-citation and bibliographic coupling analyses, we unveil the origins and evolution of collaborative networks over time by analysing the references from the most important academic contributions. Our goal is threefold: first, to systematise the state of the art in the Input-Process-Output (IPO) framework; second, to elucidate the antecedents of the research field on collaborative networks (research streams originating from the field, main authors and journals) by organising them in six thematic clusters; and third, to show how the antecedents shaped the IPO framework. While ‘collaborative networks’ used to belong to two distinct domains, the research agendas seem to converge because of the interactions between their most active authors. As such, cross-fertilisation occurs with the International Journal of Production Research, which plays a central role in this process.     

Author co-citation analysis of semiconductor literature

The purpose of this study is to map semiconductor literature by author co-citation analysis in order to highlight major subject specializations in semiconductors and identify authors and their relationships within these specialties and within the field. Forty-six of the most productive authors were included in the sample list. Author samples were gathered from the INSPEC database from 1978 to 1997. The relatively low author co-citation frequencies indicate that there is a low connection among authors who publish in semiconductor journals and big differences among authors' research areas. Six sets of authors with co-citation greater than 100 times are M. Cardona and G. Lucovsky; T. Ito and K. Kobayashi; M. Cardona and G. Abstreiter; A. Y. Cho and H. Morkoc; C. R. Abernathy and W. S. Hobson; H. Morkoc and I. Akasaki. The Pearson correlation coefficient of author co-citation varies widely, i.e., from -0.17 to 0.92. This shows that some authors with high positive correlations are related in certain ways and co-cited, while other authors with high negative correlations may be rarely or never related and co-cited. Cluster analysis and multi-dimensional scaling are employed to create two-dimensional maps of author relationships in the cross-citation networks. It is found that the authors fall fairly clearly into three clusters. The first cluster covers authors in physics and its applications. The authors in the second group are experts in electrical and electronic engineering. The third group includes specialists in materials science. Because of its interdisciplinary nature and diverse subjects, semiconductor literature lacks a strong group of core authors. The field consists of several specialties around a weak center. This revised version was published online in June 2006 with corrections to the Cover Date.     

Journal co-citation analysis of semiconductor literature

The purpose of this study is to map semiconductor literature using journal co-citation analysis. The journal sample was gathered from the INSPEC database from 1978 to 1997. In the co-citation analysis, the data compiled were counts of the number of times two journal titles were jointly cited in later publications. It is assumed that the more two journals are cited together, the closer the relationship between them. The journal set used was the 30 most productive journals in the field of semiconductors. Counts of co-citations to the set of semiconductor journals were retrieved from SciSearch database, accessed through Dialog. Cluster analysis and multi-dimensional scaling were employed to create two-dimensional maps of journal relationships in the cross-citation networks. The following results were obtained through this co-citation study: The 30 journals fall fairly clearly into three clusters. The major cluster of journals, containing 17 titles, is in the subject of physics. The second cluster, consisting of 9 journals, includes journals primarily on material science. The remaining cluster represents research areas in the discipline of electrical and electronic engineering. All co-cited journals share similar co-citation profiles, reflected in high positive Pearson correlation. Two hundred and ninety-six pairs (68%) correlate at greater than 0.70. This shows that there is strong relationship between semiconductor journals. Five individual journals in five paired sets with co-citation frequency over 100,000 times include Physical Review B, Condensed Matter; Physical Review Letters; Applied Physics Letters; Journal of Applied Physics; and Solid State Communications. This revised version was published online in August 2006 with corrections to the Cover Date.     

Literature review on the ‘Smart Factory’ concept using bibliometric tools

The objective of this paper is to depict a landscape of the scientific literature on the concept of the ‘Smart Factory’, which in recent years is gaining more and more attention from academics and practitioners because of significant innovations in the production systems within the manufacturing sector. To achieve this objective, a dynamic methodology called ‘Systematic Literature Network Analysis (SLNA)’ has been applied. This methodology combines the Systematic Literature Review approach with the analysis of bibliographic networks. The adopted methodology allows complementing traditional content-based literature reviews by extracting quantitative information from bibliographic networks to detect emerging topics, and by revealing the dynamic evolution of the scientific production of a discipline. This dynamic analysis allowed highlighting research directions and critical areas for the development of the ‘Smart Factory’. At the same time, it offers insights on the fields on which companies, associations, politicians and technology providers need to focus in order to allow a real transition towards the implementation of large-scale Smart Factory.     

Related records retrieval and pennant retrieval: an exploratory case study

The Related Records feature in the Web of Science retrieves records that share at least one item in their reference lists with the references of a seed record. This search method, known as bibliographic coupling, does not always yield topically relevant results. Our exploratory case study asks: How do retrievals of the type used in pennant diagrams compare with retrievals through Related Records? Pennants are two-dimensional visualizations of documents co-cited with a seed paper. In them, the well-known tf*idf (term frequency*inverse document frequency) formula is used to weight the co-citation counts. The weights have psychological interpretations from relevance theory; given the seed, tf predicts a co-cited document’s cognitive effects on the user, and idf predicts the user’s relative ease in relating its title to the seed’s title. We chose two seed papers from information science, one with only two references and the other with 20, and used them to retrieve 50 documents per method in WoS for each of our two seeds. We illustrate with pennant diagrams. Pennant retrieval indeed produced more relevant documents, especially for the paper with only two references, and it produced mostly different ones. Related Records performed almost as well on the paper with the longer reference list, improving remarkably as the coupling units between the seed and other papers increased. We argue that relevance rankings based on co-citation, with pennant-style weighting as an option, would be a desirable addition to WoS and similar databases.

     

Using ‘core documents’ for detecting and labelling new emerging topics

The notion of ‘core documents’, first introduced in the context of co-citation analysis and later re-introduced for bibliographic coupling and extended to hybrid approaches, refers to the representation of the core of a document set according to given criteria. In the present study, core documents are used for the identification of new emerging topics. The proposed method proceeds from independent clustering of disciplines in different time windows. Cross-citations between core documents and clusters in different periods are used to detect new, exceptionally growing clusters or clusters with changing topics. Three paradigmatic types of new, emerging topics are distinguished. Methodology is illustrated using the example of four ISI subject categories selected from the life sciences, applied sciences and the social sciences.