• Journal of the Korean Society for information Management
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• v.29 no.2
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• pp.193-204
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• 2012

The characteristics of citation and centrality measures in citation networks can be identified using multiple linear regression analyses. In this study, we examine the relationships between bibliometric indices and centrality measures in an article-level co-citation network to determine whether the linear model is the best fitting model and to suggest the necessity of data transformation in the analysis. 703 highly cited articles in Physics published in 2004 were sampled, and four indicators were developed as variables in this study: citation counts, degree centrality, closeness centrality, and betweenness centrality in the co-citation network. As a result, the relationship pattern between citation counts and degree centrality in a co-citation network fits a non-linear rather than linear model. Also, the relationship between degree and closeness centrality measures, or that between degree and betweenness centrality measures, can be better explained by non-linear models than by a linear model. It may be controversial, however, to choose non-linear models as the best-fitting for the relationship between closeness and betweenness centrality measures, as this result implies that data transformation may be a necessary step for inferential statistics.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.4
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• pp.269-284
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• 2022

Exploring research similarity of researchers offers insight on research communities and potential interactions among scholars. While co-authorship is a popular measure for studying research similarity of researchers, it cannot provide insight on authors who have not collaborated yet. In this work, we present novel approach to capture research similarity of authors using citation information. Extensive study is conducted on DATA & KNOWLEDGE ENGINEERING (DKE) publications to demonstrate and compare suggested approach with co-authorship based approach. Analysis result shows that proposed approach distinguishes author relationships that is not shown in co-authorship network.

• Journal of the Korean Society for information Management
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• v.33 no.2
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• pp.201-225
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• 2016

A new technique for revealing the research fronts of a interdisciplinary discipline has been developed. Citation image makers profiling (CIMP) determines the relationships between research papers with the title words of the citing documents. We adapted this new technique to analyze the research fronts and hot topics in women's studies of Korea. By Korean Citation Index (KCI) data in 2015, we selected 148 papers cited more than 9 times as the core documents of women's studies. Analysis of intellectual structure using citation image makers profiling was performed with the 148 core documents and those citing papers. Document co-citation analysis was hindered by citation data sparsity, while CIMP method successfully revealed the structure of research fronts of Korean women's studies including 2 divisions and 6 subdivisions. The CIMP method suggested in this study has good potential to discover the characteristics of research fronts of interdisciplinary research domains.

• Journal of the Korean Society for Library and Information Science
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• v.22
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• pp.331-360
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• 1992

This research presents author co-citation analysis of the subject area in the humanities - Korean history. Three approaches to multivariate analyses were used to display the inter-author relationships in the similarity matrix. Data on co-citation of sixty seven authors for the period of 1980­1989 were extracted from the database constructed by author. The author's name, here refers to a body of writings by a person, is the unit of analysis. The data were subjected to non-metric multidimensional scaling program create two-dimensional map of authors. Authors with similarity are clustered using hierarchical agglomerative procedure and it is found that five clusters in Korean history represent primarily research specializations. Author map of Korean history reveals the first dimension corresponding to subject orientation of authors and the second dimension corresponds to research method or research style. In factor analysis, each factor reflects research specialty made up of authors, and factor locadings demonstrate the breadth or concentration of sixty seven authors' scholarly contributions on Korean history. It is demonstrated that the· specific methodology employed by this research, author co-citation analysis, is useful to represent the intellectual structure of Korean history.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4467-4488
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• 2014

The bibliometric analysis is widely used for understanding research domains, trends, and knowledge structures in a particular field. The analysis has majorly been used in the field of information science, and it is currently applied to other academic fields. This paper describes the analysis of academic literatures for classifying research domains and for suggesting empty research areas in the telecommunications policy. The application software is developed for retrieving Thomson Reuters' Web of Knowledge (WoK) data via web services. It also used for conducting text mining analysis from contents and citations of publications. We used three text mining techniques: the Keyword Extraction Algorithm (KEA) analysis, the co-occurrence analysis, and the citation analysis. Also, R software is used for visualizing the term frequencies and the co-occurrence network among publications. We found that policies related to social communication services, the distribution of telecommunications infrastructures, and more practical and data-driven analysis researches are conducted in a recent decade. The citation analysis results presented that the publications are generally received citations, but most of them did not receive high citations in the telecommunications policy. However, although recent publications did not receive high citations, the productivity of papers in terms of citations was increased in recent ten years compared to the researches before 2004. Also, the distribution methods of infrastructures, and the inequity and gap appeared as topics in important references. We proposed the necessity of new research domains since the analysis results implies that the decrease of political approaches for technical problems is an issue in past researches. Also, insufficient researches on policies for new technologies exist in the field of telecommunications. This research is significant in regard to the first bibliometric analysis with abstracts and citation data in telecommunications as well as the development of software which has functions of web services and text mining techniques. Further research will be conducted with Big Data techniques and more text mining techniques.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.79-86
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• 2019

It is very important to analyze and provide information resources for research output produced in the computer field, the core science of the 4th Industrial Revolution. In this paper, SCI journals cited from domestic journals in the computer field were identified and the citation rankings and their co-citation networks were generated, analyzed, mapped and visualized. For this, the bibliographic and citation index information from 2015 to 2017 in the KSCD were used as the basis data, and the co-citation method and network centrality analysis were used. As a result of this study, the number of citations and the citation ranks of SCI journals and papers cited by korean journals in the computer field were analyzed, and peak time(2 years), half-life(6.6 years), and immediacy citation rate(2.4%) were measured by citation age analysis. As a result of network centrality analysis, Three network centralities(degree, betweenness, closeness) of the cited SCI journals were calculated, and the ranking of journals by each network centrality was measured, and the relationship between the subject classifications of the cited SCI journals was visualized through the mapping of the network.

• Journal of the Korean Society for information Management
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• v.32 no.4
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• pp.77-106
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• 2015

By document co-citation analysis with Korean Citation Index (KCI) data, this study accurately identified the research fronts and hot topics in Korean library and information science (LIS) from 2004 to 2013. 159 core papers in LIS domain and their citations are scraped manually from Korean Citation Index web site. In the cluster analysis and network analysis, 159 core papers were grouped into 27 clusters with multiple papers and 8 singlton clusters. Among the 27 clusters which have multple papers, 'LIS education' cluster was the largest with 16 core papers, and 'citation analysis & intellectual structure analysis' cluster had the strongest citation impact according to the ehs-index. Closer observation of the citations to the core papers in each research front showed that 67.5% of the citations were made by LIS research papers and 32.5% of the citations were made by non-LIS research papers. Considering the share of citations and the citation impact growth index, 'local documentation', 'citation analysis & intellectual structure analysis', and 'research trends analysis' were identified as the most emerging research front in Korean library and information science. The analytical methods used in this study have great potential in discovering the characteristics of research fronts in Korean interdisciplinary research domains.

• Journal of the Korean Society for information Management
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• v.34 no.3
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• pp.109-124
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• 2017

Through a wide variety of disciplines, practices on data access and re-use have been increased recently. In fact, there has been an emerging phenomenon that researchers tend to use the data sets produced by other researchers and give scholarly credit as citation. With respect to this practice, in 2012, Thomson Reuters launched Data Citation Index (DCI). With the DCI, citation to research data published by researchers are collected and analyzed in a similar way for citation to journal articles. The purpose of this study is to identify the characteristics and intellectual structure of sociology field based on research data, which is one of actively data-citing fields. To accomplish this purpose, two data sets were collected and analyzed. First, from DCI, a total of 8,365 data were collected in the field of sociology. Second, a total of 12,132 data were collected from Web of Science with a topic search with 'Sociology'. As a result of the co-word analysis of author provided-keywords for both data sets, the intellectual structure of research data-based sociology was composed of two areas and 15 clusters and that of article-based sociology was composed with three areas and 17 clusters. More importantly, medical science area was found to be actively studied in research data-based sociology and public health and psychology are identified to be central areas from data citation.

• English Language & Literature Teaching
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• v.10 no.3
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• pp.113-126
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• 2004

Explicit reference to the work of other authors is an essential feature of most academic research writings. Corpus analysis of academic text can reveal much about what writers actually do and why they do so. Application of corpus tools in language education has been well documented by many scholars (Pedersen, 1995, Swales, 1990, Thompson, 2000). They demonstrate how computer technology can assist in the effective analysis of corpus based data. For teaching purposes, tills recent research provides insights in the areas of English for Academe Purposes (EAP). The need for such support is evident when students have to use appropriate citations in their writings. Using Swales' (1990) division of citation forms into integral and non-integral and Thompson and Tnbble's (2001) classification scheme, this paper codifies academic texts in a corpus. The texts are academic research articles from different disciplines. The results lead into a comparison of the citation practices m different disciplines. Finally, it is argued that the information obtained in this study is useful for EAP writing courses in EFL countries.

• Journal of Technology Innovation
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• v.13 no.3
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• pp.197-224
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• 2005

Recently, the notion of National Innovation System (NIS) has attracted considerable attention as a key driver of the economic success. Amongst others, the Northeast Asian countries deserve highlight as central cases of NIS. This research attempts to examine inter-industrial knowledge flows and structure among Northeast Asian countries. To this end, Korea, Japan and Taiwan are selected and the patent citation data, a proxy of disembodied knowledge flows, from United Stated Patents and Trademark Office (USPTO) are employed for cluster analysis and network analysis. Some meaningful findings are presented and distinctive characteristics of respective countries are contrasted.