The proximity of co-citation

Traditional co-citation analysis has not taken the proximity of co-cited references into account. As long as two references are cited by the same article, they are retreated equally regardless the distance between where citations appear in the article. Little is known about what additional insights into citation and co-citation behaviours one might gain from studying distributions of co-citation in terms of such proximity. How are citations distributed in an article? What insights does the proximity of co-citation provide? In this article, the proximity of a pair of co-cited reference is defined as the nearest instance of the co-citation relation in text. We investigate the proximity of co-citation in full text of scientific publications at four levels, namely, the sentence level, the paragraph level, the section level, and the article level. We conducted four studies of co-citation patterns in the full text of articles published in 22 open access journals from BioMed Central. First, we compared the distributions of co-citation instances at four proximity levels in journal articles to the traditional article-level co-citation counts. Second, we studied the distributions of co-citations of various proximities across organizational sections in articles. Third, the distribution of co-citation proximity in different co-citation frequency groups is investigated. Fourth, we identified the occurrences of co-citations at different proximity levels with reference to the corresponding traditional co-citation network. The results show that (1) the majority of co-citations are loosely coupled at the article level, (2) a higher proportion of sentence-level co-citations is found in high co-citation frequencies than in low co-citation frequencies, (3) tightly coupled sentence-level co-citations not only preserve the essential structure of the corresponding traditional co-citation network but also form a much smaller subset of the entire co-citation instances typically considered by traditional co-citation analysis. Implications for improving our understanding of underlying factors concerning co-citations and developing more efficient co-citation analysis methods are discussed.     

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.     

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.     

Knowledge-transfer analysis based on co-citation clustering

Based on co-citation cluster analysis, we propose a knowledge-transfer analysis model for any technology field. In this model, patent data with backward citations to non-patent literature and forward citations by later patents would be analyzed. Co-citation clustering of the cited articles defines scientific knowledge sources, while that of the patents themselves defines technology fronts. According to the citation between the article and patent clusters, the landscape of knowledge-transfer including route and strength between scientific knowledge sources and technology fronts can be mapped out. The model has been applied to the field of transgenic rice. As a result of the analysis, ten scientific knowledge sources and eight technology fronts have emerged, and reasonable links between them have been established, which clearly show how knowledge has been transferred in this field.     

Patent co-citation networks of Fortune 500 companies

This paper provides an overview of the progression of technology structure based on patent co-citation networks. Methods of patent bibliometrics, social network analysis and information visualization are employed to analyze patents of Fortune 500 companies indexed in Derwent Innovations Index, the largest patent database in the world. Based on the co-citation networks, several main technology groups are identified, including Chemicals, Petroleum Refining, Motor Vehicles, Pharmaceuticals, Electronics, etc. Relationships among the leading companies and technology groups are also revealed.     

Analysis of citation and co-citation in chemical engineering

This paper presents the results of the citation study in 24 leading journals on chemical engineering for 1987. The selective methodology or the analysis of co-citation limited only to this discipline is based on relatively low thresholds of citation and co-citation. The established research fronts refer mostly to basic research. The flow of information and knowledge to chemical engineering is determined to the extent of 70–90% by the works in this very field, as is indicated by the analysis of citations. The geography of research fronts was determined. The USSR has a very low fraction of frontal papers. This can be explained by the publication of papers in Russian and by a large number of secondary and applied research. This type of research is revealed by frequent citation of books and a small fraction of highly cited papers.     

A comparative study of first and all-author co-citation counting,and two different matrix generation approaches applied for author co-citation analyses

Aim  The present article contributes to the current methodological debate concerning author co-citation analyses. (ACA) The study compares two different units of analyses, i.e. first- versus inclusive all-author co-citation counting, as well as two different matrix generation approaches, i.e. a conventional multivariate and the so-called Drexel approach, in order to investigate their influence upon mapping results. The aim of the present study is therefore to provide more methodological awareness and empirical evidence concerning author co-citation studies. Method  The study is based on structured XML documents extracted from the IEEE collection. These data allow the construction of ad-hoc citation indexes, which enables us to carry out the hitherto largest all-author co-citation study. Four ACA are made, combining the different units of analyses with the different matrix generation approaches. The results are evaluated quantitatively by means of multidimensional scaling, factor analysis, Procrustes and Mantel statistics. Results  The results show that the inclusion of all cited authors can provide a better fit of data in two-dimensional mappings based on MDS, and that inclusive all-author co-citation counting may lead to stronger groupings in the maps. Further, the two matrix generation approaches produce maps that have some resemblances, but also many differences at the more detailed levels. The Drexel approach produces results that have noticeably lower stress values and are more concentrated into groupings. Finally, the study also demonstrates the importance of sparse matrices and their potential problems in connection with factor analysis. Conclusion  We can confirm that inclusive all-ACA produce more coherent groupings of authors, whereas the present study cannot clearly confirm previous findings that first-ACA identifies more specialties, though some vague indication is given. Most crucially, strong evidence is given to the determining effect that matrix generation approaches have on the mapping of author co-citation data and thus the interpretation of such maps. Evidence is provided for the seemingly advantages of the Drexel approach.     

Citation context analysis of a co-citation cluster: Recombinant-DNA

The techniques of co-citation clustering and citation context analysis are combined to concretely define the shared knowledge within a research specialty. The cluster for a large and fast moving biomedical specialty, recombinant-DNA, is presented in terms of the highly cited documents comprising it and their co-citation links. By examining citation contexts in the papers citing the highly cited documents, it is possible to label each of the documents in the cluster with its specific cognitive meaning for the citing authors. Co-citation contexts are used to reveal the relationships among the concepts symbolized by the highly cited documents, providing a cognitive equivalent of the co-citation links. This may open a new way to the investigation of the logic of conceptual change at the specialty level.     

Fractal geometry of information space as represented by co-citation clustering

In this paper we discuss geometrical properties of information space as represented by the phenomenon of co-citation clustering. More specifically, the size distribution of co-citation clusters is studied and interpreted in terms of fractal dimensions.     

Sleeping beauties with no prince based on the co-citation criterion

In science, a sleeping beauty (SB) refers to a highly cited paper that initially remains unnoticed for several years after publication. It is generally recognized that each SB is awoken by princes, in the form of other papers that cite the SB. Investigations have shown that one feature of a prince is that it has a considerable number of co-citations with the SB. In the present study, we applied a method to screen for princes from among papers citing the SB based on the number of co-citations in the Web of Science and identified four SBs that were awoken without a prince based on the co-citation criterion. There are two possible explanations for this phenomenon. The first is that some SBs may not need a prince to attract the attention of other academics. The authors of three of the four abovementioned SBs were Nobel laureates, and their work was well known in their respective fields. The papers had slept for a long period because their work was ahead of its time. The long period of sleep is a reflection of the authors’ high academic level and degree of insight. The other potential explanation is that princes do not have to be co-cited with SBs. Our findings demonstrate a significant deficiency in the previous criteria relating to princes based on co-citations. Thus, new criteria are required to identify princes.

     

The dynamic capabilities perspective of strategic management: a co-citation analysis

Scientometrics - Dynamic capabilities currently emerge as a vibrant field of study within the theoretical framework based on resource and strategic management. To this end, and as a complex field...     

A journal co-citation analysis of library and information science in China

This paper aims to reveal the relationship and structure of library and information science (LIS) journals in China. 24 core LIS journals in China are selected and the relevant data of journal co-citation are retrieved from Chinese Journal Full-Text Database constructed by China National Knowledge Infrastructure during the period of 1999–2009. By calculating mean co-citation frequencies and correlation coefficients, we find that there is a strong relationship among LIS journals in China. Utilizing the methods of cluster analysis, multidimensional scaling analysis and factor analysis, we analyze the data of journal co-citation. LIS journals in China are divided into four clusters. The relatedness among journals is shown manifestly through their locations in the two-dimensional map. A three-factor solution is obtained with the factor loading of each journal. Finally, we interpret and discuss the results to get some conclusions and also expect to describe the network characters of journal co-citation in future research.     

Using the appearance of citations in full text on author co-citation analysis

As a frequently used method of depicting scientific intellectual structures, author co-citation analysis (ACA) has been applied to many domains. However, only count-based information is involved as the input of ACA, which is not sufficiently informative for knowledge representations. This article catches several metadata in full text of citing papers but not aims at content-level information, which increases the amount of information input to ACA without increasing computational complexity a lot. We propose a new method by involving information including the number of mentioned times in a citing paper and the number of context words in a citing sentence. We combine these pieces of information into the traditional ACA and compare the results between ACA and the proposed approach by using factor analysis, network analysis, and MDS-measurement. The result of our empirical study indicates that compared with the traditional ACA, the proposed method shows a better clustering performance in visualizations and reveals more details in displaying intellectual structures.     

Exploring the modelling and simulation knowledge base through journal co-citation analysis

Co-citation analysis is a form of content analysis that can be applied in the context of scholarly publications with the purpose of identifying prominent articles, authors and journals being referenced to by the citing authors. It identifies co-cited references that occur in the reference list of two or more citing articles, with the resultant co-citation network providing insights into the constituents of a knowledge domain (e.g., significant authors and papers). The contribution of the paper is twofold; (a) the demonstration of the added value of using co-citation analysis, and for this purpose the underlying dataset that is chosen is the peer-reviewed publication of the Society for Modeling and Simulation International (SCS)—SIMULATION; (b) the year 2012 being the 60th anniversary of the SCS, the authors hope that this paper will lead to further acknowledgement and appreciation of the Society in charting the growth of Modeling and Simulation (M&S) as a discipline.     

Macro-level changes in the structure of co-citation clusters: 1983–1989

At ISI we have used a consistent method for clustering the combinedScience Citation Index andSocial Sciences Citation Index for the last seven years (1983 to 1989). This method involves clustering highly cited documents by single-link clustering and then clustering the resultant clusters, a total of four times. This gives a hierarchical or nested structure of clusters four levels deep. Relationships among clusters at a given level can be depicted by multidimensional scaling, and by comparing successive year maps we can see how the relationships of major disciplines have changed from year to year. We focus mainly on the two highest levels of aggregation, C4 and C5, to make observations about structural changes in science involving the major disciplines. Distinction is made between changes which appear to be cyclic or oscillatory in nature, and those which appear to be more permanent or unidirectional.     

Climate change and interdisciplinarity: a co-citation analysis of IPCC Third Assessment Report

This study addresses whether interdisciplinarity is a prominent feature of climate research by means of a co-citation analysis of the IPCC Third Assessment Report. The debate on interdisciplinarity and bibliometric measures is reviewed to operationalize the contested notion of interdisciplinarity. The results, based on 6417 references of the 96 most frequently used journals, demonstrate that the IPCC assessment of climate change is best characterized by its multidisciplinarity where the physical, biological, bodily and societal dimensions are clearly separated. Although a few fields and journals integrate a wide variety of disciplines, integration occurs mainly between related disciplines (narrow interdisciplinarity) which indicate an overall disciplinary basis of climate research. It is concluded that interdisciplinarity is not a prominent feature of climate research. The significance of this finding is explored, given that the problem scope of climate change necessitates interdisciplinarity. Ways to promote interdisciplinarity are suggested by way of conclusion.     

A transition stage co-citation criterion for identifying the awakeners of sleeping beauty publications

Scientometrics - The role played by citing papers in triggering the recognition of sleeping beauty (SB) papers may be concealed by the traditional co-citation criteria for screening awakeners for...