• Journal of the Korean Society for Library and Information Science
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• v.32 no.3
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• pp.23-44
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• 1998

This study dealt with author production, subject production, university production and research method for the purpose of clarifying the LIST research pattern of us by using the method of content analysis of 1,855 items of monographic which have been published in Korea between 1957 and december of 1997. It also analyzed and core special subject, core author, core author in each special part and language analysis quantitatively through the data. This study was done to apprehend the core subject and area, distribution of the subject and the general research pattern of Library and Information science.

• Journal of the Korean Society for information Management
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• v.25 no.2
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• pp.143-155
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• 2008

Authoritative as well as objective information on ranking or dominant research areas of academic departments/schools in a certain discipline is essential for the graduate school applicants. In this study, we performed an informetric analysis to identify dominant research areas in the top 10 U.S. LIS schools. We used two different datasets of research productivity and research interests of the LIS faculty. The correspondence analysis method was employed to graphically display the association between research areas and the LIS schools. We found that the research Productivity data collected from SSCI database generated a very informative map presenting which research areas were dominant in which LIS schools. We also found that for the two most productive suhject areas in LIS over the past 10-year period, the proportion of research articles in information retrieval decreased to a great extent in the recent 5-rear period, whereas that of information seeking behavior showed an almost same degree of increase.

• Journal of Information Management
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• v.39 no.3
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• pp.95-113
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• 2008

In todays environment in which scientific technologies are changing very fast than ever, companies have to monitor and search emerging technologies to gain competitiveness. Actually many nations try to do that. Most of them use Dephi approach based on experts review as a searching method. But experts review has been criticised for probability of inclination and its derivative problems in the sense that it is accomplished only by expert's subjectivity. To overcome such problems, we used Scientometric Method for identifying emerging technology that had been done by Delphi as a rule. We made three particular efforts in order to improve the Quality of the result. Firstly, we selected one alternative database between SCI and Scopus hoping to see evenly-distributing results in wide fields on the front burner. Secondly we used Fractional citation counting in counting citation number in the stage of linear regression analysis. Lastly, we verified Scientometric result with experts opinions to minimize probable errors in a Scientometric research. As a result, we derived 290 emerging technologies from Scientometric analysis with Scopus Database, and visualized them on 2-dimension map with data mining system named KnowledgeMatrix which was developed by KISTI.

• Journal of Information Management
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• v.35 no.1
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• pp.93-112
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• 2004

This study is intend to analyze the cited patent life time of US patent data via more objective way. It is based on exploratory approach which is one of various methods for technology forecasting. The life spans of cited patents of specific technological field are deduced from using informetric analysis of USPA database of KISTI, which is composed of US patent data covered from 1972 to present. The statistics of the results may help to estimate the economic life span of the specific technological area for technology valuation.

• Journal of the Korean Society for information Management
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• v.41 no.1
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• pp.411-438
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• 2024

This study aims to identify and comprehensively view health information-related research trends using a bibliometric analysis. To this end, 1,193 papers from 2002 to 2023 related to "health information" were collected through the Korea Citation Index (KCI) database and analyzed in diverse aspects: research trends by period, academic fields, intellectual structure, and keyword changes. Results indicated that the number of papers related to health information continued to increase and has been decreasing since 2021. The main academic fields of health information-related research included "biomedical engineering," "preventive medicine/occupational environmental medicine," "law," "nursing," "library and information science," and "interdisciplinary research." Moreover, a co-word analysis was performed to understand the intellectual structure of research related to health information. As a result of applying the parallel nearest neighbor clustering (PNNC) algorithm to identify the structure and cluster of the derived network, four clusters and 17 subgroups belonging to them could be identified, centering on two conglomerates: "medical engineering perspective on health information" and "social science perspective on health information." An inflection point analysis was attempted to track the timing of change in the academic field and keywords, and common changes were observed between 2010 and 2011. Finally, a strategy diagram was derived through the average publication year and word frequency, and high-frequency keywords were presented by dividing them into "promising," "growth," and "mature." Unlike previous studies that mainly focused on content analysis, this study is meaningful in that it viewed the research area related to health information from an integrated perspective using various bibliometric methods.

• Journal of Korean Library and Information Science Society
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• v.38 no.2
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• pp.31-50
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• 2007

This paper presents a scientometric analysis of the growth of literature output in the field of Hepatitis covered in three bibliographic databases namely MEDLINE, CINAHL and IPA. The literature covered in three databases for the period 1984-2003 was considered. MEDLINE covered the maximum of 75750 records during the study period 1984 to 2003. This is followed by CINAHL and IPA databases. It is found that the annual growth rate of literature in a particular field of knowledge will not be uniform and in order to measure the rate of growth from year after year, the application of RGR is quite appropriate. The RGR has shown a decreasing trend, with a slight fluctuation of growth rate for the years 1985 and 1997. The output by colleges, universities, corporate sector and research institutions with reference to RGR and Dt has shown mixed results such as increasing trend, decreasing trend and fluctuation trend. Hepatitis research indicates a different picture when the RGR and Dt were calculated by year-wise both in terms of number of papers and number of pages.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.68-74
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• 2008

Application areas of Knowledge Discovery in Database(KDD) have been expanded to many R&D management processes including technology trends analysis, forecasting and evaluation etc. Established research field such as informetrics (or scientometrics) has utilized techniques or methods of KDD. Various systems have been developed to support works of analyzing large-scale R&D related databases such as patent DB or bibliographic DB by a few researchers or institutions. But extant systems have some problems for korean users to use. Their prices is not moderate, korean language processing is impossible, and user's demands not reflected. To solve these problems, Korea Institute of Science and Technology Information(KISTI) developed stand-alone type information analysis system named as KnowledgeMatrix. KnowledgeMatrix system offer various functions to analyze retrieved data set from databases. KnowledgeMatrix's main operation unit is composed of user-defined lists and matrix generation, cluster analysis, visualization, data pre-processing. Matrix generation unit help extract information items which will be analyzed, and calculate occurrence, co-occurrence, proximity of the items. Cluster analysis unit enable matrix data to be clustered by hierarchical or non-hierarchical clustering methods and present tree-type structure of clustered data. Visualization unit offer various methods such as chart, FDP, strategic diagram and PFNet. Data pre-processing unit consists of data import editor, string editor, thesaurus editor, grouping method, field-refining methods and sub-dataset generation methods. KnowledgeMatrix show better performances and offer more various functions than extant systems.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.1
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• pp.167-198
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• 2022

Convergence science research is activated, and digital humanities research is also encouraged in humanities. Therefore, this study attempted to propose a experimental study that applies Text mining and Entitymetrics methods to historical materials. Annals of King Seonjo, revised Annals of King Seonjo, Miscellaneous Record of the War and Writings on Imjin War were used, also network analysis and DMR topic models were used to explore topic changes and common entities in historical sources. Through the results, it was possible to propose the availability of quantitative analysis for text data, presenting a timing change of a specific topic, and an undiscovered relationship between person entities.

• Journal of the Korean Society for information Management
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• v.31 no.3
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• pp.293-311
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• 2014

This study explored the research trends on Twitter in Korea by informetric methods. All 539 articles on Twitter published from 2009 to the April of 2014 were obtained from the KCI. Only article titles, abstracts, and keywords by authors were used in analysis. Academic journals in many different disciplines where Twitter articles were produced were analysed by profiling, and then, the subject areas of researches on Twitter were analysed by co-word analysis. The results of this study showed that Twitter-related papers were published in as many as 53 disciplines with journalism, business administration, and computer science to be core fields. It was also found that the core subject areas are political issues and business.

• Proceedings of the Korean Society for Information Management Conference
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• 2006.08a
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• pp.121-126
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• 2006

이 연구에서는 인터넷 자원을 통해 사회과학 분야의 학제성을 측정하고 그 특징을 알아보기 위해 세 가지 계량정보학적 분석을 수행하였다. 먼저 세계적인 사회과학 정보 게이트웨이인 SOSIG의 Grapevine 자료를 통해 사회과학 내 학문분야 간 학제성을 측정하였고, 관련 학자들의 홈페이지 동시링크와 미국 상위 관련 학과 홈페이지의 동시링크를 분석하였다. 그 결과 business, education, philosophy 등을 중심으로 어느 정도 학제성이 나타났으나, 심리학 등 사회과학의 몇몇 분야의 학제성은 예상 외로 높지 않은 것으로 나타났다.