• Journal of the Korean Society for Library and Information Science
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• v.53 no.3
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• pp.25-43
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• 2019

Recently there has been a growing interest in digital preservation and digital curation with rapid increase of digital resource. This study aims to investigate the research topics and the course topics related digital preservation and digital curation. The course information is collected from the curricular of library and information science departments and archival science departments in leading countries such as US, England, Ireland, Canada and New Zealand. Title keyword profiling and network analysis were adapted to discover core research and education areas. The key topics in the abstracts of research papers and the contents of the course were also illustrated by these methods. In the research analysis, archival system is the biggest area of researches related digital preservation and digital curation. Courser analysis shows digital curation education and process is the important area of education. As a result of content analysis, plan and strategy is a notable topic of research and record management process is a major topic of courses for digital preservation and digital curation. In addition, format of digital resource is an important topic for research and courses.

• 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 the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.564-568
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• 2011

Microblogs became popular information delivery ways due to the spread of smart phones. They have the characteristic of reflecting the interests of users more quickly than other medium. Particularly, in case of the subject which attracts many users, microblogs can supply rich information originated from various information sources. Nevertheless, it has been considered as a hard problem to obtain useful information from microblogs because too much noises are in them. So far, various methods are proposed to extract and track some subjects from particular documents, yet these methods do not work effectively in case of microblogs which consist of short phrases. In this paper, we propose a graph-based topic extraction and partitioning method to understand interests of users about a certain keyword. The proposed method contains the process of generating a keyword graph using the co-occurrences of terms in the microblogs, and the process of splitting the graph by using a network partitioning method. When we applied the proposed method on some keywords. our method shows good performance for finding a topic about the keyword and partitioning the topic into sub-topics.

• Journal of the Korean Society for information Management
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• v.38 no.3
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• pp.23-39
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• 2021

This study aims to explore research trends in Blockchain studies in South Korea using dynamic topic modeling and network analysis. To achieve this goal, we conducted the university & institute collaboration network analysis, the keyword co-occurrence network analysis, and times series topic analysis using dynamic topic modeling. Through the university & institute collaboration network analysis, we found major universities such as Soongsil University, Soonchunhyang University, Korea University, Korea Advanced Institute of Science and Technology (KAIST) and major institutes such as Ministry of National Defense, Korea Railroad Research Institute, Samil PricewaterhouseCoopers, Electronics and Telecommunications Research Institute that led collaborative research. Next, through the analysis of the keyword co-occurrence network, we found major research keywords including virtual assets (Cryptocurrency, Bitcoin, Ethereum, Virtual currency), blockchain technology (Distributed ledger, Distributed ledger technology), finance (Smart contract), and information security (Security, privacy, Personal information). Smart contracts showed the highest scores in all network centrality measures showing its importance in the field. Finally, through the time series topic analysis, we identified five major topics including blockchain technology, blockchain ecosystem, blockchain application 1 (trade, online voting, real estate), blockchain application 2 (food, tourism, distribution, media), and blockchain application 3 (economy, finance). Changes of topics were also investigated by exploring proportions of representative keywords for each topic. The study is the first of its kind to attempt to conduct university & institute collaboration networks analysis and dynamic topic modeling-based times series topic analysis for exploring research trends in Blockchain studies in South Korea. Our results can be used by government agencies, universities, and research institutes to develop effective strategies of promoting university & institutes collaboration and interdisciplinary research in the field.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.92-104
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• 2021

This study aims to analyze online news articles to identify social issues related to patient safety and compare the changes in these issues before and after the implementation of the Patient Safety Act. This study performed text mining through the R program, wherein 7,600 online news articles were collected from January 1, 2010, to March 5, 2020, and examined using keyword analysis, topic modeling, and word co-occurrence network analysis. A total of 2,609 keywords were categorized into 8 topics: "medical practice", "medical personnel", "infection and facilities", "comprehensive nursing service", "medicine and medical supplies", "system development and establishment for improvement", "Patient Safety Act" and "healthcare accreditation". The study revealed that keywords such as "patient safety awareness", "infection control" and "healthcare accreditation" appeared before the implementation of the Patient Safety Act. Meanwhile, keywords such as "patient safety culture". and "administration and injection" appeared after the act's implementation with improved ranking of importance pertaining to nursing-related terminology. Interest in patient safety has increased in the medical community as well as among the public. In particular, nursing plays an important role in improving patient safety. Therefore, the recognition of patient safety as a core competency of nursing and the persistent education of the public are vital and inevitable.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.5
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• pp.55-72
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• 2016

This study aims at providing a methodology for retaining international technology competitiveness, marketable industry, and sustainable promising technology in a field of new growth engine industry such as national unmanned aerial vehicle industry. We draw a result by analysing with tools such as KrKwic, Excel, NetMiner, presenting methods of a Social Network Analysis, sub-group analysis, and cognitive map analysis based on patent data in a field of unmanned aerial vehicle industry. As a result, some future promising technologies are prospected as what worths concentrated investment, such as 'pilot control tech', 'identification of friend or foe tech'.

• Journal of Digital Convergence
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• v.17 no.12
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• pp.509-521
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• 2019

The purpose of this study is to examine the patterns of the keywords in journals in the field of Cognitive Behavioral Therapy (CBT) to identify the knowledge structure of CBT studies in Korea. To compare CBT studies from Korea and abroad, 234 articles (2008-2019) published on "Cognitive Behavior Therapy in Korea" and 2,316 articles (1977-2019) published on "Cognitive Therapy and Research" were collected. The data were analyzed using NetMiner 4.3. The co-word analysis was done by calculating the cosine similarity matrix of major keywords, followed by visualizing the network. The results of this study identified the main interests of Korean CBT scholars, and categorized the knowledge structure of CBT in Korea into 9 research areas: "scale validation"; "perfectionism and entrapment"; "cognitive, emotional, and relationship characteristics of schizophrenic patients"; "cognitive characteristics and treatment of borderline personality disorder and depression/bipolar disorder patients"; "adaptation and psychological health"; "cognitive characteristics and treatment of patients with social anxiety disorder"; "causes and co-morbidities of depression"; "acceptance and commitment therapy"; and "understanding and the treatment of binge eating disorder patients." This study is meaningful in that it has reviewed the accumulated knowledge in the CBT field in Korea for the past 11 years, and suggests future tasks for development to improve the standards of CBT practice.

• Journal of the Korean Society for Library and Information Science
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• v.50 no.2
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• pp.289-307
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• 2016

Infectious diseases such as Ebola virus disease become a social issue and draw public attention to be a major topic on news or research. As a result, there have been a lot of studies on infectious diseases using text-mining techniques. However, there is no research on content analysis of two media channels that have distinct characteristics. Accordingly, in this study, we conduct topic analysis between news (representing a social perspective) and academic research paper (representing perspectives of bio-professionals). As text-mining techniques, topic modeling is applied to extract various topics according to the materials, and the word co-occurrence map based on selected bio entities is used to compare the perspectives of the materials specifically. For network analysis, topic map is built by using Gephi. Aforementioned approaches uncovered the difference of topics between two materials and the characteristics of the two materials. In terms of the word co-occurrence map, however, most of entities are shared in both materials. These results indicate that there are differences and commonalties between social and academic materials.

• Journal of Korea Technology Innovation Society
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• v.20 no.4
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• pp.1015-1035
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• 2017

This paper analyzes how the concept of 'technological innovation' has changed in South Korea. We conducted keyword co-occurrence network analysis on articles in Science and Technology, a magazine published by the Korean Federation of Science and Technology Societies since 1968. With writers and readership from professional science and technology communities, government officers, as well as citizens, Science and Technology is a suitable archival source to represent discourses relating to South Korean use of the term 'technological innovation'. We used all the articles from 1968 to 2017 that include the term 'technological innovation' in their title. Also, we analyzed the keywords that co-occur with 'technological innovation' by the frame divided into three periods. The following conclusions were elicited: The term 'technological innovation' has been understood as a leading factor for government-driven industrial development since the 1960s. Nevertheless, the meaning of the term evolved over time. In the 1960s and 70s, 'technological innovation' referred to the introduction, assimilation, and transfer of technology. However, since the 1980s it has acquired a more multilateral meaning, connecting various industrial sectors and interest groups. This conclusion reveals that the meaning of 'technological innovation' is not static, but rather it is constructed over time. This study is expected to contribute to research on the direction of the technological innovation policy of Korea.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.5
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• pp.413-422
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• 2022

Smart farms are receiving a lot of attention as a way to solve the chronic labor shortage and aging problems in agriculture. The smart farm industry, called the 6th industrial revolution, needs to strengthen its competitiveness. In order to apply innovative IT technology to agriculture, it is important to collect and analyze information about prior research or patents. This paper examines smart farm patent trends through 5,789 patent data related to smart farm using the domestic patent information search service(KIPRIS). This paper examines the domestic patent trends of smart farm information through keyword network, ego network, simultaneous appearance network, and bigram network analysis. As a result of network analysis related to smart farm patents, patents related to smart farm systems and control technologies were the most common. This paper can provide help in setting the direction of future smart farm-related patent research.