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.     

Visualizing the structure and bridges of the intellectual property management and strategy literature: a document co-citation analysis

This article uses document co-citation analysis to objectively explore the underlying structure of the intellectual property research domain, taken from a managerial and strategic standpoint. The goal of this study is identifying its main research areas, understanding its current state of development and suggesting potential future directions, by analyzing the co-citations from 181 papers published between 1992 and 2011 in the most influential academic journals. Five main clusters have been identified, mapped, and labeled as follows: Economics of patent system, technological and institutional capabilities, university patenting, intellectual property exploitation, and division of labor. Their most active areas on this topic, and the most influential and co-cited papers have been identified and described. Also, intra- and inter-cluster knowledge base diversity has been assessed by using indicators stemming from the domains of information theory and biology. A t test has been performed to assess the significance of the inter-cluster diversity. The knowledge bases of these five clusters are significantly diverse, this meaning that they are five co-existing paradigms.     

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.     

Discovering related scientific literature beyond semantic similarity: a new co-citation approach

Scientometrics - Mendeley is a social network that allows researchers worldwide to discover, search and share resources and to cooperate with peer researchers. We can recognize a large amount of...     

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.     

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.     

Evaluations of context-based co-citation searching

Since machine-readable documents have become widespread, some recent studies have proposed retrieval methods using a combination of citation linkage and its context. In the case of co-citation linkage, there have been attempts to discern ‘strong’ co-citations from ‘weak’ ones by examining the positions of citations in a document. However, this promising concept has not yet been sufficiently evaluated, and it remains unclear whether search performance is significantly improved. Therefore, this paper explores the effects of using co-citation context more deeply and more widely by comparing the search performance of six retrieval methods, which differ as to whether co-citation context and normalization using cited frequency are used. For empirically evaluating the effects, a special test collection was created from CiteSeer Metadata, and the search performances of the six retrieval methods were compared by two IR metrics (AP and nDCG). The main conclusions of this paper are: (1) co-citation context has a positive effect on co-citation searching; (2) the normalization technique using cited frequency is useful for context-based co-citation searching; (3) approaches of using co-citation context tend to affect the characteristics of search performance.     

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.     

Understanding rapid theoretical change in particle physics: A month-by-month co-citation analysis

While co-citation analysis nas proved a powerful tool in the study of changes in intellectual foci in science, the technique has never been used to study very rapid changes in the theoretical structure of a scientific field. In this paper we present month-by-month co-citation analyses of key phases in the weak-electromagnetic unification research program within particle physics and show that these analyses capture and illuminate very rapid intellectual changes. These data provide yet another illustration of the utility of co-citation analysis for understanding the history of science.An earlier version of this paper was published inInformation Choices and Policies (Knowledge Industries Publications, Inc., White Plains, N. Y.: 1979), Vol. 16, Proceedings of the 42nd Annual Meeting of the American Society for Information Science. Knowledge Industries and the ASIS have kindly given permission to us to seek a wider audience. This work was made possible by NSF Grant GS-41697 to the Research Program on Social Analyses of Science Systems (SASS), Cornell University, Ithaca, New York and NSF Grant SOC76-84482 to Carleton College, Northfield, Minnesota.     

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.     

Applying author co-citation analysis to user interaction analysis: a case study on instant messaging groups

Author co-citation analysis (ACA) was an important method for discovering the intellectual structure of a given scientific field. There was sufficient experience that ACA would work with almost any user data that lent itself to co-occurrence. While most of the current researches still relied on the data of scientific literatures. In this study, in order to provide useful information for better enterprise management, the idea and method of ACA was applied to analyze the information interaction intensity and contents of enterprise web users. Firstly, the development of ACA was briefly introduced. Then the sample data and method used in this study were given. Three QQ groups’ instant messages of a Chinese company were selected as the raw data and the concepts and model of user interaction intensity (UII) were proposed by referring the ACA theory. Social network analysis method, combined with in-deep interview method were used to analyze the information interaction intensity and contents of enterprise users. Operatively, Excel, Ucinet, Pajek, Netdraw and VOSviewer software were combined to analyze them quantitatively and visually. Finally, it concluded that UII model was relatively reasonable and it could nicely measure the information interaction intensity and contents of enterprise web users.     

The interdisciplinary structure of research on intercultural relations: a co-citation network analysis study

This study aims to map the content and structure of the knowledge base of research on intercultural relations as revealed in co-citation networks of 30 years of scholarly publications. Source records for extracting co-citation information are retrieved from Web of Science (1980–2010) through comprehensive keyword search and filtered by manual semantic coding. Exploratory network and content analysis is conducted (1) to discover the development of major research themes and the relations between them over time; (2) to locate representative core publications (the stars) that are highly co-cited with others and those (the bridges) connecting more between rather than within subfields or disciplines. Structural analysis of the co-citation networks identifies a core cluster that contains foundational knowledge of this domain. It is well connected to almost all the other clusters and covers a wide range of subject categories. The evolutionary path of research themes shows trends moving towards (e.g. psychology and business and economics) and away from (e.g. language education and communication) the core cluster over time. Based on the results, a structural framework of the knowledge domain of intercultural relations research is proposed to represent thematic relatedness between topical groups and their relations.     

Exploring evolution and emerging trends in business model study: a co-citation analysis

This paper is an early attempt of using co-citation analysis to sort out and to analyze the development and evolution of a latest hot area, business model. A dataset of 1498 records published between 1995 and 2015 is collected from Web of Science database. The empirical results show the latest hot topics in the business model study focus on business model innovation and value creation. In addition, technology oriented articles and strategy oriented articles provide some of the main perspectives of business model study. The conclusions and implications of business model in this paper will be particularly illuminating for both academic research and enterprises’ practice application.     

Citation and co-citation analysis to identify core and emerging knowledge in electronic commerce research

The purpose of this paper is to explore the core and emerging knowledge of electronic commerce (e-commerce) research. Data was collected from the top six e-commerce journals from 2006–2010. A total of 1,064 electronic commerce related articles and 33,173 references were identified. There were 48 high value research articles identified using a citation and co-citation analysis. Using statistical analysis including factor analysis, multidimensional scaling, and cluster analysis, we identified five research areas: trust, technology acceptance and technology application, e-commerce task-related application, e-markets, and identity and evaluation. We also identified emerging core knowledge, information systems success. The findings of this study provide core knowledge and directions for researchers and practitioners interested in the electronic commerce 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.