• Journal of the Korean Society for Library and Information Science
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• v.40 no.2
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• pp.333-355
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• 2006

Network generation methods to visualize bibliometric data for examining the intellectual structure of knowledge domains are investigated in some detail. Among the four methods investigated in this study, pathfinder network algorithm is the most effective method in representing local details as well as global intellectual structure. The nearest neighbor graph, although never used in bibliometic analysis, also has some advantages such as its simplicity and clustering ability. The effect of input data preparation process on resulting intellectual structures are examined, and concluded that unlike MDS map with clusters, the network structure could be changed significantly by the differences in data matrix preparation process. The network generation methods investigated in this paper could be alternatives to conventional multivariate analysis methods and could facilitate our research on examining intellectual structure of knowledge domains.

• Journal of the Korean Society for information Management
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• v.22 no.2 s.56
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• pp.205-228
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• 2005

This research analyzed changes of the intellectual structure of web information by examining time changes and search engines using the co-links analysis. According to the results, the co-links web information clusters on the two maps appeared to contain changes in the intellectual structure over the two time periods. The intellectual structure that appeared in the information map for AltaVista and MSN Search engines was relatively similar. However. there were also cases where the clusters of some web information was different. The results of the research revealed that the cocitation analysis could be applied simultaneously to diachronous analysis in the web information.

• Journal of the Korean Society for Library and Information Science
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• v.39 no.3
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• pp.207-224
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• 2005

This study investigated the intellectual structure of records management and archives field in Korea and America using author cocitation analysis. Major journals in the field from 2000 to 2004 are used to select frequent cited authors. Cocited authors are analyzed in details by means of multi-variate statistical techniques such as multidimensional scaling. To the analysis of this intellectual structure, main research topics in Korea were laws and policies related to records management and archives whereas information technology based electronic records management in America.

• Journal of the Korean Society for Library and Information Science
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• v.43 no.3
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• pp.417-439
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• 2009

In this study, the intellectual structure of Records Management and Archival Science in Korea was analyzed based on the syntactic and semantic structure analysis of article titles. The data used in this study were 344 articles from three major representative journals in the field of Records Management and Archival Science, published from 1999 to 2008. The results of the syntactic and semantic structure analysis of article titles show that the three role concepts of keywords are 'research domain', 'research object', and 'research focus'. Keywords in article titles were clustered into the core subject areas after they were assigned three concepts. Based on the results of cluster analysis, the intellectual structure of Records Management and Archival Science in Korea was proposed.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.2
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• pp.147-178
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• 2021

In this study, co-word analysis was conducted to investigate the intellectual structure of the domestic open access area. Through KCI and RISS, 124 research articles related to open access in Korea were selected for analysis, and a total of 1,157 keywords were extracted from the title and abstract. Network analysis was performed on the selected keywords. As a result, 3 domains and 20 clusters were extracted, and intellectual relations among keywords from open access area were visualized through PFnet. The centrality analysis of weighted networks was used to identify the core keywords in this area. Finally, 5 clusters from cluster analysis were displayed on a multidimensional scaling map, and the intellectual structure was proposed based on the correlation between keywords. The results of this study can visually identify and can be used as basic data for predicting the future direction of open access research in Korea.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.3
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• pp.103-129
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• 2021

This study examined the characteristics of two keyword types expressing the topics in the intellectual structure analysis based on the co-word analysis, focused on overseas open access field. Specifically, the keyword set extracted from the LISTA database in the field of library and information science was divided into two types (controlled keywords and uncontrolled keywords), and the results of performing intellectual structure analysis based on co-word analysis were compared. As a result, the two keyword types showed significant differences by keyword sets, research maps and influences, and periods. Therefore, in intellectual structure analysis based on co-word analysis, the characteristics of each keyword type should be considered according to the purpose of the study. In other words, it would be more appropriate to use controlled keywords for the purpose of examining the overall research trend in a specific field from the perspective of the entire academic field, and to use uncontrolled keywords for the purpose of identifying detailed trends by research area from the perspective of the specific field. In addition, for a comprehensive intellectual structure analysis that reflects both viewpoints, it can be said that it is most desirable to compare and analyze the results of using controlled keywords and uncontrolled keywords individually.

• Journal of the Korean Society for information Management
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• v.30 no.2
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• pp.207-225
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• 2013

Due to the development of science and technology, the convergence of various disciplines has been fostered. Accordingly, interdisciplinary studies have increasingly been expanded by integrating knowledge and methodology from different disciplines. The primary focus of biblimetric methods is on investigating the intellectual structure a field, and analysis of the characterization of interdisciplinary studies is overlooked. In this study, we aim to identify the intellectual structure of the field of medical informatics through author co-citation analysis and co-word analysis by the representative journal "IEEE ENG MED BIOL." In addition, we examine authors and MeSH Terms of top three representative journals for further analysis of the field. We examine the intellectual structure of the medical informatics field by author and word clusters to identify the network structure of medical informatics disciplines.

• Journal of Korean Academy of Nursing
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• v.41 no.1
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• pp.129-140
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• 2011

Purpose: This study was done to develop an instrument for measuring intellectual capital and assess its validity and reliability in identifying the components, human capital, structure capital and customer capital of intellectual capital in hospital nursing organizations. Methods: The participants were 950 regular clinical nurses who had worked for over 13 months in 7 medical hospitals including 4 national university hospitals and 3 private university hospitals. The data were collected through a questionnaire survey done from July 2 to August 25, 2009. Data from 906 nurses were used for the final analysis. Data were analyzed using descriptive statistics, Cronbach's alpha coefficients, item analysis, factor analysis (principal component analysis, Varimax rotation) with the SPSS $PC^+$ 17.0 for Windows program. Results: Developing the instrument for measuring intellectual capital in hospital nursing organizations involved a literature review, development of preliminary items, and verification of validity and reliability. The final instrument was in a self-report form on a 5-point Likert scale. There were 29 items on human capital (5 domains), 21 items on customer capital (4 domains), 26 items on structure capital (4 domains). Conclusion: The results of this study may be useful to assess the levels of intellectual capital of hospital nursing organizations.

• Journal of the Korean Society for information Management
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• v.23 no.4 s.62
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• pp.215-231
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• 2006

Recently there are many bibliometric studies attempting to utilize Pathfinder networks(PFNets) for examining and analyzing the intellectual structure of a scholarly field. Pathfinder network scaling has many advantages over traditional multidimensional scaling, including its ability to represent local details as well as global intellectual structure. However there are some limitations in PFNets including very high time complexity. And Pathfinder network scaling cannot be combined with cluster analysis, which has been combined well with traditional multidimensional scaling method. In this paper, a new method named as Parallel Nearest Neighbor Clustering (PNNC) are proposed for complementing those weak points of PFNets. Comparing the clustering performance with traditional hierarchical agglomerative clustering methods shows that PNNC is not only a complement to PFNets but also a fast and powerful clustering method for organizing informations.

• Journal of the Korean Society for information Management
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• v.34 no.4
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• pp.101-126
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• 2017

Data Science is emerging as a closely related field of study to Library and Information Science (LIS), and as an interdisciplinary subject combining LIS, statistics and computer science in an attempt to understand the value of data by applying what LIS has been doing for collecting, storing, organizing, analyzing, and utilizing information. To investigate which subject fields other than LIS, statistics, and computer science are related to Data Science, this study retrieved 667 materials from Web of Science Core Collection, extracted terms representing Web of Science Categories, examined subject fields that are studying Data Science using descriptive analysis, analyzed the intellectual structure of the field by co-word analysis and network analysis, and visualized the results as a Pathfinder network with clustering created with the PNNC clustering algorithm. The result of this study might help to understand the intellectual structure of the Data Science field, and may be helpful to give an idea for developing relatively new curriculum.