• Journal of Korean Library and Information Science Society
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• v.53 no.1
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• pp.191-210
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• 2022

Niklas Luhmann is a sociologist who has had a strong influence on other disciplines. Therefore, it is necessary to examine what Luhmann's theory has influenced on his subsequent researchers. This study analyzed the knowledge network of studies on Niklas Luhmann's theory by follow-up researchers. Bibliographic coupling and co-citation were used as the analysis method of knowledge network. The main results are as follows. First, the language clusters were divided into Latin American / Spanish-speaking regions, Western Europe / Anglo-American regions, Eastern / Northern Europe and other language regions through bibliographic coupling analysis. Second, from the node analysis of bibliographic coupling, It was divided into 2 main cases: where Luhmann's major works were cited; where Luhmann's minor works were cited. Third, it was found that there are the core work groups that are repeatedly cited among Luhmann's works. Fourth, 12 core works were derived from the node analysis of the co-citation network, and appeared in four groups according to themes.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.28 no.2
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• pp.149-154
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• 2017

Objectives: The purpose of this study is to analyze the co-author networks in the Journal of the Korean Academy of Child and Adolescent Psychiatry, a representative journal published by a branch of the domestic psychiatric academy, in order to present the current state of the co-authoring of and developments in child and adolescent psychiatry. Methods: We visualized and estimated the basic characteristics of the co-author networks shown by 564 authors who wrote 251 papers published in the Journal of the Korean Academy of Child and Adolescent Psychiatry between 2005 and 2015, in order to assess their network characteristics, author centrality, and relevance to research performance. Results: The co-author networks in the Journal of the Korean Academy of Child and Adolescent Psychiatry showed the characteristics of a small world and scale-free network. There was a correlation between the author centrality within the network and the research performance of the authors, but less correlation was shown between the centrality and mean paper citation counts. Conclusion: The network structure in the Journal of the Korean Academy of Child and Adolescent Psychiatry showed similarity to the co-authoring of other branches. However, given that the mean paper citation counts were less correlated with the author centrality than those in other branches, it may be necessary to promote an increase in the mean paper citation counts.

• Journal of Digital Convergence
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• v.14 no.9
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• pp.301-308
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• 2016

Writing high-quality papers and publishing them at prestigious academic journals would be something that every scholar strives for. This study made a network with nine academic journals in South Korea in the field of public administration and public policy and analyzed the influence of academic journals through social network analysis. Using centrality measures, such as degree centrality, beta centrality, and eigenvector centrality, this study found that Korean Public Administration Review has the highest influence on the journal network, followed by Korean Public Studies Review. However, different choice of centrality measure led to different ranking of journals in terms of their influence.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.18-29
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• 2022

The purpose of this exploratory study is to examine the intellectual structure of data science. For this purpose, this research examined a total of 17,997 bibliographies on data science indexed in Web of Science(WoS) of Clarivate Analytics from 2012 to 2021. This research applied methods such as descriptive analysis, citation analysis, co-author network analysis, co-occurrence network analysis, bibliographic coupling analysis, and co-citation analysis. This research contributes to finding the research directions of future data science topics.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5227-5237
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• 2011

Technology roadmap is a powerful tool that considers relationships of technology, product and market and referred as a supporting technology strategy and planning. There are numerous studies that have attempted to develop technology roadmap and case studies on specific technology areas. However, a number of studies have been dependant on brainstorming and discussion of expert group, delphi technique as qualitative analysis rather than systemic and quantitative analysis. To overcome the limitation, patent analysis considered as quite quantitative analysis is employed in this paper. Therefore, this paper proposes new technology roadmapping based on patent citation network considering technology life cycle and suggests planning for undeveloped technology but considered as promising. At first, patent data and citation information are collected and patent citation network is developed on the basis of collected patent information. Secondly, we investigate a stage of technology in the life cycle by considering patent application year and the technology life cycle, and duration of technology development is estimated. In addition, subsequent technologies are grouped as nodes of a super-level technology to show the evolution of the technology for the period. Finally, a technology roadmap is drawn by linking these technology nodes in a technology layer and estimating the duration of development time. Based on technology roadmap, technology planning is conducted to identify undeveloped technology through text mining and this paper suggests characteristics of technology that needs to be developed in the future. In order to illustrate the process of the proposed approach, technology for hydrogen storage is selected in this paper.

• Journal of the Korean Society for information Management
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• v.32 no.4
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• pp.205-221
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• 2015

The impact of a journal is commonly used as the impact of an individual paper within that journal. It is problematic to interpret a journal's impact as a single paper's impact of the journal, so there are several researches to measure a single paper's impact with its own citation counts. This study applied 8 impact indicators to Korean Citation Index database and examined discipline bias of each indicator. Analyzed indicators are simple citation counts, PageRank, f-value, CCI, c-index, single publication h-index, single publication hs-index, and cl-index. PageRank has the least discipline bias at highly ranked papers and journal bias in a discipline. On the contrary, simple citation counts showed strongly biased results toward a certain discipline or a journal. KCI database provides only simple citation counts. It needs to show PageRank (global indicator) to discover influential papers in diverse areas. Furthermore it needs to consider to provide the best of local indicators. Local indicators can be calculated only with papers in users' search results because they uses citation counts of citing papers and the number of references. They are more efficient than global indicators which explore the whole database. KCI should also consider to provide Cl-index (local indicator).

• Asia pacific journal of information systems
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• v.31 no.3
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• pp.358-377
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• 2021

Knowledge drives business innovation. However, even if companies have the same knowledge element in the business ecosystem, innovation performance varies depending on the structural position of the technical knowledge network. This study investigated whether there is a difference in exploitative innovation according to the structural position of the AI technical knowledge network. We collected patents from the top 100 digital companies registered with the US Patent Office from 2015 to 2019 and classified the companies into knowledge producer-based brokers, knowledge absorber-based brokers, knowledge absorbers, and knowledge producers from the perspective of knowledge creation and flow. The analysis results are as follows. First, a few of the top 100 digital companies disseminate, absorb, and mediate knowledge, while the majority do not. Second, exploitative innovation is the largest, in the order of knowledge producer, knowledge absorber-based broker, knowledge absorber, and knowledge producer-based broker. Finally, patents for industrial intelligence occupy a large proportion, and knowledge producers are leading exploitative innovation. Therefore, latecomers need to expand their resources and capabilities by citing patents owned by leading companies and converge with existing industries into AI-based industries.

• Agribusiness and Information Management
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• v.3 no.1
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• pp.23-37
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• 2011

The development of informatization impacts all sectors, including agriculture. Agricultural informatization builds the knowledge linkage structures of agricultural innovation systems globally. This study investigated the global knowledge linkage structures in agricultural innovation pertinent to information technology (IT) for agricultural research and development (R&D) investments and activities. We explored the longitudinal trend of systemness within the networked research relationships in the triple helix (TH) of the university, industry and government (UIG). We collected data from publications in the Science Citation Index (SCI), the Social Sciences Citation Index (SSCI), and the Arts and Humanities Citation Index (A&HCI) to analyze the TH network dynamics. We also performed a scientometrics analysis to quantitatively identify the knowledge and insights of global agricultural innovation structures. These results could be informative for individual countries. Our findings reveal that the global knowledge linkage structures in the agricultural sector that are pertinent to IT fluctuate widely and fail to increase the capacity of agricultural innovation research due to a neglect of the network effects of the TH dynamics of UIG.

• 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.

• The Journal of Information Systems
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• v.28 no.3
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• pp.39-58
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• 2019

Purpose A digital twin is a digital replication of a physical system. Gartner identified the digital twin as one of the Gartner Top 10 Strategic Technology Trend for three years from 2017. The rapid development of the digital twin market is expected to bring about innovation and change throughout society, and much research has been done recently in academia. In this research, we tried to explore the main research trends for digital twin research. Design/methodology/approach We collected the digital twin research from Web of Science, and analyzed 804 articles that was published during time span of 2010-2018. A total of 41 key authors were selected based on the frequency of citation. We created a co-citation matrix for the core authors, and performed multivariate analysis such as cluster analysis and multidimensional scaling. We also conducted social network analysis to find the influential researchers in digital twin research. Findings We identified four major sub- areas of digital twin research: "Infrastructure", "Prospects and Challenges", "Security", and "Smart Manufacturing". We also identified the most influential researchers in digital twin research: Lee EA, Rajkumar R, Wan J, Karnouskos S, Kim K, and Cardenas AA. Limitation and further research suggestion were also discussed as a concluding remarks.