• The Journal of Internal Korean Medicine
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• v.43 no.6
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• pp.1075-1088
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• 2022

Objectives: The aim of this study is to analyze cancer research trends in traditional Korean medical journals indexed in the Korea Citation Index since 2000. Methods: Cancer research papers published in traditional Korean medical journals were searched in databases from inception to October 2022. The numbers of publications by journal and by year were descriptively assessed. After natural language processing, topic modeling (based on Latent Dirichlet allocation) and keyword network analysis were conducted. Results: This research trend analysis involved 1,265 papers. Six topics were identified by topic modeling: case reports on symptom management, literature reviews, experiments on apoptosis, herbal extract treatments of breast carcinoma cell lines, anti-proliferative effects of herbal extracts, and anti-tumor effects. Keyword network analysis found that the effects of herbal medicine were assessed in clinical and experimental studies, while acupuncture was mainly mentioned in clinical reports. Conclusions: Cancer research papers in traditional Korean medical journals have contributed to evidence-based medicine. Further experimental studies are needed to elucidate the effects of on different hallmarks of cancer. Rigorous clinical studies are needed to support clinical guidelines.

• Journal of Korea Technology Innovation Society
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• v.17 no.2
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• pp.334-354
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• 2014

This study aims to analyze the research trend of Korean medicine based on social network analysis. To do this, a dataset has been collected from KCI (Korea Citation Index) database. According to the results, we have identify the longitudinal trend of the number of papers, journals, organizations and key words in this field. Moreover, based on the nodes' centrality of co-author network, we have found a core journal (i.e. Korean Journal of Oriental Physiology and Pathology), a hub institution (i.e. Kyunghee university) and two main key words (i.e. anti-oxidation and acupuncture) in the research network. In conclusion, integrating field experts' tacit knowledge in Korean medicine studies with the results of the explicit social network analysis on the research trend, we put forward further policy implications with regard to R&D strategies in this field.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.135-144
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• 2022

This study explores that how the logic of network power in the existing digital content distribution structure works against local media. The limitless citation of local media content, in particular, is becoming more common in order to profit from network traffic while not giving appropriate remuneration for local media content. This study tried to demonstrate how network media dominance alienates local media material by using YouTube network analysis of TV Maile Shinmun. According to the research result, it was found that major news media tends to take profits from the local media interview by not properly indicating the source video, or reporting the core content of the local media interview, making it unnecessary to look for the original video source. Despite the viewpoint that the digital environment presents opportunities for local media, the current network logic would not benefit local media, which calls for the need that the digital content distribution strategy of local media develops a new order such as NFT, one of blockchain-based monetary system.h the help of information technology.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2089-2094
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• 2017

Altmetrics is the measurement index and quantitative data to complement the traditional indicators based on the citation. Altmetrics research has acquired greater importance in the past few years, partly due to the complement to the traditional bibliometrics. This paper aims to reveal the research status and trends in altmetrics research. A total of 187 articles from 2005 to 2017 are obtained and analyzed, illustrating a steady rise (S-mode) in altmetrics research since 2005. Using social network analysis and co-word analysis, the author cooperation network and keyword co-occurrence network are developed. The core scientists and eight international research groups are discovered, reflecting that researchers in this field have a low degree of cooperation. Four topics of altmetrics research are discovered by hierarchical clustering. The results can be useful for the advanced research of altmetrics.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.706-710
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• 2006

Recently, several studies have been carried on knowledge flow of science, technology, industry to establish STI policy. Still it is lack of studies on relationship of science-industry although there have been studied only in aspect of science-technology relationship or technology-industry relationship. This paper's purpose is to propose method to measure knowledge flow among science, technology, and industry by means of patent citation. After gathering knowledge flow data between science and technology through mapping citing patent and cited paper, it gets knowledge flows data between technology-industry by using OTC (OECD Technology Concordance), technology-industry mapping program. Basd on 2 types of knowledge flow data, it propose method to examine knowledge flow from science to industry by applying overlap function is a network link weight function.

• Journal of Information Management
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• v.41 no.2
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• pp.1-30
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• 2010

This study analyzed research output in dominant research areas of 19 national research institutions. Policy knowledge produced by the institutions during the past 5 years mainly concerned 10 policies dealing with economy and society issues. Similarities between the research subjects of the institutions were displayed by MDS mapping. The study also identified issue attention cycles of the 5 chosen policies and examined the correlation between the issue attention cycles and the yields of policy knowledge. The knowledge structure of each policy was mapped using co-word analysis and Ward's clustering. It was also found that the institutions performing research on similar subjects demonstrated citation preferences for each other.

• Journal of Korea Technology Innovation Society
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• v.14 no.spc
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• pp.1171-1186
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• 2011

Identifying Emerging Technology Trends is crucial for decision makers of nations and organizations in order to use limited resources, such as time, money, etc., efficiently. Many researchers have proposed emerging trend detection systems based on a popularity analysis of the document, but this still needs to be improved. In this paper, an emerging trend detection classifier is proposed which uses both academic and industrial data, SCOPUS and PATSTAT. Unlike most pre-vious research, our emerging technology trend classifi-er utilizes supervised, semi-automatic, machine learning techniques to improve the precision of the results. In addition, the citation information from among the SCOPUS data is analyzed to identify the early signals of emerging technology trends.

• Journal of Digital Convergence
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• v.14 no.12
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• pp.121-131
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• 2016

This research aims to analyze domestic articles related to entrepreneurship and elicit implications for future research. To this end, bibliometric analysis was conducted for the authors and titles of 1,887 articles published in the Korean Citation Index between 1997 and 2016. First, in the author analysis, Dae Yong Chung, Bong Sik Bin & Jeong Ki Park, and Sung Sik Bahn were noticeable in terms of the number of articles, the number of citation and the formation of the researchers' network. Second, in the title analysis, the characteristics of entrepreneurs and education in entrepreneurship, entrepreneurial strategies and case studies, the empirical analyses regarding entrepreneurial performance, investment in startups, and Korean IT companies were found to be the most active research fields. The results of this study can be used in selecting co-researchers and exploring research areas in the future.

• Journal of Contemporary Eastern Asia
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• v.18 no.1
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• pp.7-29
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• 2019

This study describes an approach for comparative bibliometric analysis of scientific publications related to (i) individual or several departments comprising a university, and (ii) broader integrated subject areas using multiple disciplinary schemes. It uses a custom dataset of scientific publications (ca. 15,000 articles and reviews, published during 2009-2013, and recorded in the Web of Science Core Collections) with author affiliations to the research departments, dedicated to science, technology, engineering, mathematics, and medicine (STEMM), of a comprehensive university. The dataset was subjected, at first, to the department level and discipline level analyses using the newly available KAKEN-L3 classification (based on MEXT/JSPS Grants-in-Aid system), hierarchical clustering, correspondence analysis to decipher the major departmental and disciplinary clusters, and visualization of the department-discipline relationships using two-dimensional stacked bar diagrams. The next step involved the creation of subsets covering integrated subject areas and a comparative analysis of departmental contributions to a specific area (medical, health and life science) using several disciplinary schemes: Essential Science Indicators (ESI) 22 research fields, SCOPUS 27 subject areas, OECD Frascati 38 subordinate research fields, and KAKEN-L3 66 subject categories. To illustrate the effective use of the science mapping techniques, the same subset for medical, health and life science area was subjected to network analyses for co-occurrences of keywords, bibliographic coupling of the publication sources, and co-citation of sources in the reference lists. The science mapping approach demonstrates the ways to extract information on the prolific research themes, the most frequently used journals for publishing research findings, and the knowledge base underlying the research activities covered by the publications concerned.

• Journal of Information Science Theory and Practice
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• v.8 no.4
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• pp.40-54
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• 2020

This proposed work aims to understand the Korean Academic Circle (KAC)'s research trend on the "One Belt One Road" (OBOR) by employing a quantitative analysis of the recent research articles published by the KAC. To do so, this proposed research has used the well-known network analysis software, Ucinet 6, by which the papers on related topics are collected and filtered from Korea Citation Index. To perform the analytical selection, the proposed work has chosen 'keywords' as the core research object and performed analysis from transverse to longitudinal aspects, and from holistic to individual aspects, respectively; and from this, the KAC's research trend on OBOR is derived. The present work has established that the KAC's attention is continuously increasing on OBOR and has sustainability. Centered on the OBOR, Korean researchers have spread their studies in various dimensions ranging from the issues like China's political economy to Sino-Korea economic and trade exchanges, and so on. The KAC has even combined OBOR with Korea's international development initiatives, which can help Korea benefit from active and sustainable cooperation with China. Moreover, the proposed work has found that Korean researchers have also actively expressed their growing attention, highlighted Korea's interest, and showed concern about China hegemony and Sinocentrism in their recent documented research works.