• Journal of Korean Society of Archives and Records Management
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• v.24 no.1
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• pp.89-109
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• 2024

The study analyzed the research trends of domestic and international record information services from 2003 to 2022. A total of 136 academic papers registered in the Korea Citation Index (KCI) and 74 from the Library, Information Science & Technology Abstracts (LISTA) were examined by quantitative and qualitative content analysis to understand the research status of 20 years from various angles, such as publication year, research type, researcher type, subject, and purpose. Frequency analysis, co-occurrence frequency analysis, centrality analysis, and topic modeling were performed by applying text mining techniques. Results showed that domestic papers demonstrated a research flow focused on specific institutions or records, and user-centered satisfaction surveys and content-centered studies were conducted. Moreover, foreign papers confirmed various evaluation-oriented and information provision studies, such as data, resources, and collections, along with the research trend focusing on the relationship between archivists and users. The management of information resources was identified as a common topic in both domestic and foreign papers, but it is possible to identify that domestic research focuses on maintaining the quality of domestic information resources, while foreign research focuses on the storage and retrieval of information.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.28 no.1
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• pp.191-207
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• 2017

This paper employs entitymetrics analysis on the research works of Dong-ju Yun. He was a Korean poet who was studied by many researchers on his works, religion and life. We collected 1,076 papers about Dong-ju Yun and conducted various approaches including co-author citation analysis, topic modeling analysis to identify the topic trend in the study of Dong-ju Yun. Also we extracted entities like person's name and literature's title from abstract to examine the relationship among them. The result of this paper enables us to objectively identify the topic trend and infer implicit relationships between key concept associated with Dong-ju Yun based on text data. Moreover, we observed sub-research topics such as life, poem, aesthetic existence, comparative literature, literary translation, and religious beliefs. This paper shows how entitymetrics can be utilized to study intellectual structures in the humanities.

• Journal of Technology Innovation
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• v.24 no.4
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• pp.249-275
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• 2016

For the past 50 years, innovation field has gone through an evolution. The range of research topics on innovation has expanded and diversified, along with a quantitative increase. In a multi-disciplinary field like innovation, to explore new topics and understand research trends, it is necessary to possess a comprehensive understanding regarding the current status of, and trends in, the research. In this study, the research trend in innovation studies from 2000 to 2015 was analyzed in a holistic perspective. For this, a novel technique, text mining was used. The result shows that innovation studies has focused on the traditional and emerging topics. Also, the differentiations has appeared in some of the traditional topics. This study provides not only an understanding of research dynamics, but also an opportunity to gain insights into the evolution of a new paradigm from an academic perspective.

• The Journal of the Korea Contents Association
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• v.17 no.8
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• pp.490-505
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• 2017

The purpose of this study was to analyze the research trend of transformational leadership published in domestic journals in the last 10 years and to find some implications for future research. For this purpose, 337 research papers on transformational leadership from 2007 to 2016 were reviewed. This study used descriptive statistics by frequency and percentage and a network text analysis method. The findings of the study are as follows. First, the annual average number of papers published was 33. Second, 'human resource management research' was the most common topic. Third, most of the research subjects were business employees. Fourth, the research method trend analysis showed that the highest proportion was in the quantitative research. Fifth, 'transactional leadership' showed the highest frequency as a result of analyzing the keywords presented in the abstract of the paper. Sixth, as a result of analyzing the network texts, those having the trend of being analyzed with a close connections were 'transactional leadership', which had the highest connection to transformational leadership, showing the closest relationship with 'role satisfaction'.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.415-423
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• 2017

This study explored research trends by investigating articles published in the Journal of Korean Society of Fashion Design from 2001 through 2015. English key words and abstracts were analyzed using text mining and topic modeling techniques. The findings are as followings. By the text mining technique, 183 core terms, appeared more than 30 times, were derived from 7137 words used in total 338 articles' key words and abstracts. 'Fashion' and 'design' showed the highest frequency rate. After that, the well-received topic modeling technique, LDA, was applied to the collected data sets. Several distinct sub-research domains strongly tied with the previous fashion design field, except for topics such as fashion brand marketing and digital technology, were extracted. It was observed that there are the growing and declining trends in the research topics. Based on findings, implication, limitation, and future research questions were presented.

• Journal of Korea Technology Innovation Society
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• v.15 no.2
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• pp.345-368
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• 2012

As science and technology are the core engines of economic and social affairs, it is becoming increasingly necessary to explore new promising technologies in order to secure competitiveness in science and technology with a view to helping upgrade the country's overall competitiveness and promoting industrial development. The governments of major advanced countries provide R&D support for promising future technologies. Even in South Korea, a study is being carried out to set up a model for forecasting future technologies and reinforcing the relevant survey system. This study intends to explore methods of identifying promising future technologies in the bio-science sector, which has emerged as a new growth engine. It will use a text-mining technique to collect and analyze theses in the bio science sector. It will identify key research sectors by analyzing thesis contour lines, and then review promising future key research subjects through in-depth study.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.721-732
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• 2021

This study analyzed keywords for agricultural R&D using the textmining method to examine the trend of agricultural R&D. Data used for the analysis included R&D project information provided by NTIS, and the research and development step by year from 2003 to 2018 were classified and applied. The TF-IDF approach was used as the analysis method, and ranking was derived based on score. Furthermore, we analyzed by grouping for similar keywords. The main analysis results are as follows. First, agricultural R&D trends are changing according to the introduction of new technologies and changes in the external environment. Second, keyword changes appeared with a time lag in the R&D step. The main keywords are changing in the order of basic research - applied research - development research. Third, the main keyword of agricultural R&D was 'rice.' However, the direction and purpose of the research were changing according to changes in the domestic and foreign agricultural environments.

• Journal of The Korean Association For Science Education
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• v.40 no.1
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• pp.41-50
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• 2020

Looking at the understanding of scientific concepts from a linguistic perspective, it is very important for students to develop a deep and sophisticated understanding of words used in scientific concept as well as the ability to use them correctly. This study intends to provide the basis for productive knowledge education of scientific words by noting that the foundation of productive knowledge teaching on scientific words is not well established, and by exploring ways to teach the relationship among words that constitute scientific concept in a productive and effective manner. To this end, we extracted the relationship among the words that make up the scientific concept from the text of science textbook by using quantitative text analysis methods, second, qualitatively examined the meaning of the word relationship extracted as a result of each method, and third, we proposed a writing activity method to help improve the productive knowledge of scientific concept words. We analyzed the text of the "Force and motion" unit on first grade science textbook by using four methods of quantitative linguistic analysis: word cluster, co-occurrence, text network analysis, and word-embedding. As results, this study suggests four writing activities, completing sentence activity by using the result of word cluster analysis, filling the blanks activity by using the result of co-occurrence analysis, material-oriented writing activities by using the result of text network analysis, and finally we made a list of important words by using the result of word embedding.

• Korean Journal of Cognitive Science
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• v.13 no.3
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• pp.47-60
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• 2002

The study investigated the effects of types of presentation and cognitive load on multimedia learning. In experiment 1, subject were 90 elementary school students. The subject were assigned in three conditions: Narration and Text (NT) condition, Animation and Narration(AN) condition, Animation and Text(AT) condition. The result showed that AN condition improved the learning performances in comparison with AT condition, NT condition. Experiment 2 was administrated to 87 undergraduate students. They were participated in three conditions, also. The conditions were Animation and Text (AT) condition, Animation and Narration (AN) condition, Animation, Narration and Text (ANT) condition. the results showed that AN condition was greater in AT, ANT condition. The results from a series of these experiments imply that varying the types of presentation of identical learning materials had influences on the performances. Multimedia presentation(animation and verbal conditions) improved the learning performances in comparison with monomedia presentation(verbal condition), and the advantage was raised when learners were provided the learning material in the multimodal and multimedia environment(AN condition). Also, it came out that redundant text identical to narration disrupted learning when learners were in the picture (either animation or illustration) and narration conditions. Likewise, also for adults, performances were improved in the multimodal conditions and redundant text identical to narration was not helpful for learning. These results are evidences for the dual-coding theory and the cognitive load theory.

• Journal of Korea Port Economic Association
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• v.28 no.1
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• pp.53-82
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• 2012

The purpose of this paper is to show the clustering trend by using the context-dependent and measure-specific models for 38 Asian ports during 10 years(2001-2009) with 4 inputs and 1 output. The main empirical results of this paper are as follows. First, clustering results by using context-dependent and measure-specific models are same. Second, the most efficient clustering was shown among the Hong Kong, Singapore, Ningbo, Guangzhou, and Kaosiung ports. Third, Port Sultan Qaboos, Jeddah, and Aden ports showed the lowest level clustering. Fourth, ranking order of attractiveness is Guangzhou, Dubai, HongKong, Ningbo, and Shanghai, and the results of progressive scores confirmed that low level ports can increase their efficiency by benchmarking the upper level ports. Fifth, benchmark share showed that Dubai(birth length), and HongKong(port depth, total area, and no. of cranes) have affected the efficiency of the inefficient ports.