• Journal of the Korea Fashion and Costume Design Association
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• v.24 no.4
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• pp.73-85
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• 2022

The purpose of this study is to conduct more practical subsequent research by identifying research areas through a systematic analysis of sustainable fashion design research trends. For this study, 117 journals domestic journals published between 2010 and 2020 were selected using the keyword, 'sustainable fashion'. With the research materials, six top keywords, 'zero waste', 'sustainability', 'eco-friendly', 'upcycling', 'recycling', and 'ethical', were derived. The research status was examined by year, keyword, keyword and year, and research topic. The analysis results are as follows. First, looking into the studies by year, it was found that research on sustainable fashion increased in general. Compared to 2010, the research tripled in 2020, and it was found to have increased steadily from 2018. Second, regarding the research by keyword, eco-friendly was the most common. It can be seen that research tended to focus on recycling or eco-friendliness before, but in later material design development was heading towards upcycling. Third, concerning the research by topic, case studies were found the most before, but research on design development tended to increase recently. Based on that, it is expected that the areas of sustainable fashion design that need more research will be investigated further.

• International Journal of Contents
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• v.4 no.3
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• pp.16-19
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• 2008

The purpose of this paper is to attempt the analysis of the 'Positivist' School and the 'Interpretative' School to the Relationship between Theory and Method, Using examples from Criminological Research. The differences between approach of the positivist school and interpretative school are often made very difficult to make an approach. What are more to focus on are the relationships between quantitative research and positivism and qualitative research and interpretative paradigms are often presented as essential connections. Therefore, it is a lot more difficult to imply an appropriate research method and process depends on the subject and field of the research topic. The differences between types of research and also the connections which are made between types of research and theoretical paradigms portray a very simple picture. The danger of this is that two readily available set of research methods and assuming that positivist and interpretative research style represent competing approaches and also that they present 'either-or' alternatives as to strategies of research. For example, in some instances positivist and interpretative's methods do represent alternatives but in some case, positivist and interprativist each other can complement about each other's defects in terms of use of methodology. Though depending according to the specialist of the topic, it needs sensitivity to the potentials and the contributions of different styles of data and different methods of information collection and analysis to the criminological issues under test and to the theoretical questions being asked of them.

• Journal of the Korean Society for information Management
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• v.34 no.4
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• pp.7-32
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• 2017

Recently, deep learning has been rapidly spreading as an innovative machine learning technique in various domains. This study explored the research trends of deep learning via modified ego centered topic citation analysis. To do that, a few seed documents were selected from among the retrieved documents with the keyword 'deep learning' from Web of Science, and the related documents were obtained through citation relations. Those papers citing seed documents were set as ego documents reflecting current research in the field of deep learning. Preliminary studies cited frequently in the ego documents were set as the citation identity documents that represents the specific themes in the field of deep learning. For ego documents which are the result of current research activities, some quantitative analysis methods including co-authorship network analysis were performed to identify major countries and research institutes. For the citation identity documents, co-citation analysis was conducted, and key literatures and key research themes were identified by investigating the citation image keywords, which are major keywords those citing the citation identity document clusters. Finally, we proposed and measured the citation growth index which reflects the growth trend of the citation influence on a specific topic, and showed the changes in the leading research themes in the field of deep learning.

• Journal of the Korean Society of Physical Medicine
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• v.8 no.3
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• pp.457-466
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• 2013

PURPOSE: The purpose of this study was to investigate the trend of research in Journal of the Korean Society of Physical Medicine (JKSPM). METHODS: A total of 897 articles of JKSPM from Vol.1, No.1, 2006 to Vol.7, No.4, 2012 were reviewed in regard to research type, research level, subjects, research topic, statistic method, and researcher. RESULTS: The most common research type was experimental study(65%). The most common research level was level 2(randomized controlled trials; RCT)(55%). The most common age group of subject was age 11-30 group(55%). The most common diagnosis of subjects was stroke(49%). The main research topic of articles was therapeutic exercise(13.2%). Independent t-test was the most used statistic method. A professor was the most common researcher. The Daegu and Busan were the most common provinces that researcher works. CONCLUSION: This study showed the trend of research in JKSPM and helped readers to understand the trends of research in fields of physical therapy of Korea. In further studies, it is necessary to review systematically and intensively other journals in field of physical therapy.

• The Journal of Korean Academic Society of Nursing Education
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• v.26 no.4
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• pp.402-411
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• 2020

Purpose: The purpose of this study is to explore the trends of research related to ethical topics in Korean nursing students. Methods: A total of 131 articles that were published from 2000 to 2020 were analyzed and summarized according to publishing type, research design, subject, data analysis method, main research topic, research variables and instrument. Results: Most studies were journal articles (93.9%) and their most frequent research design was survey (75.7%). The research subjects covered all grades (35.1%) or they were divided between clinical nursing practicum (29.8%) or not (21.4%). The main research topics were biomedical ethics, ethical values, moral judgment and ethics education. Recently, ethical decision making and practical ability in nursing practice were reported. The instruments for measuring variables were limited and the same tools were used several times. Conclusion: Based on the findings of this study, it is suggested that the selection of various research topics and the application of research methods related to ethics for nursing students will continue in response to rapidly changing social phenomena in the future. In particular, it is necessary that research related to ethical and practical ability as well as ethical attitudes and perceptions of nursing students be actively carried out.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.517-528
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• 2016

This study attempted to explore and examine a new user experience (UX) research method for IoT products which are becoming widely used but lack practical user research. While user experience research has been traditionally opted for survey or observation methods, this paper utilized big data analysis method for user online reviews on an intelligent agent IoT product, Amazon's Echo. The results of topic modelling analysis extracted user experience elements such as features, conversational interaction, and updates. In addition, regression analysis showed that the topic of updates was the most influential determinant of user satisfaction. The main implication of this study is the new introduction of big data analysis method into the user experience research for the intelligent agent IoT products.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.81-89
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• 2020

The purpose of this study is to investigate science consumers' perceptions of the National Science Museum and suggest effective management strategies for the museum. Research questions were established and the analyses were conducted to achieve the research goals. The collection and analysis of the data were conducted through a new approach to image analysis that combines qualitative and quantitative methods. First, the image of the concept of science was derived from science consumers (adults, undergraduate and graduate students) through a qualitative research method (group-interviewing), and then text analysis was conducted. Second, quantitative research was conducted through LDA (Latent Dirichlet Allocation)-based topical modeling of 63,987 words extracted from 12,920 titles of blog postings from one of the most heavily-trafficked portal sites in Korea. The results of this study indicate that the perception of science differs according to the characteristics of the respondents. Further, topic-modeling extracted 20 topics from the blog posting titles and the topics were condensed into seven factors. Detailed discussions and managerial implications are provided in the conclusion section.

• The Journal of Information Systems
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• v.31 no.1
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• pp.289-304
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• 2022

Purpose The development of the network and mobile industries has induced companies to invest in information systems, leading a new industrial revolution. The Journal of Information Systems, which developed the information system field into a theoretical and practical study in the 1990s, retains a 30-year history of information systems. This study aims to identify academic values and research trends of JIS by analyzing the trends. Design/methodology/approach This study aims to analyze the trend of JIS by compounding various methods, named as TLS mining analysis. TLS mining analysis consists of a series of analysis including Term Frequency-Inverse Document Frequency (TF-IDF) weight model, Latent Dirichlet Allocation (LDA) topic modeling, and a text mining with Semantic Network Analysis. Firstly, keywords are extracted from the research data using the TF-IDF weight model, and after that, topic modeling is performed using the Latent Dirichlet Allocation (LDA) algorithm to identify issue keywords. Findings The current study used the summery service of the published research paper provided by Korea Citation Index to analyze JIS. 714 papers that were published from 2002 to 2012 were divided into two periods: 2002-2011 and 2012-2021. In the first period (2002-2011), the research trend in the information system field had focused on E-business strategies as most of the companies adopted online business models. In the second period (2012-2021), data-based information technology and new industrial revolution technologies such as artificial intelligence, SNS, and mobile had been the main research issues in the information system field. In addition, keywords for improving the JIS citation index were presented.

• Journal of the Korea Convergence Society
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• v.12 no.4
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• pp.31-42
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• 2021

The purpose of this study was to explore research topics and examine the trend in COVID19 related research papers. We identified eight topics using latent Dirichlet allocation and found acceptable validity in comparison with the structural topic model. The subtopics have been extracted using k-means clustering and plotted in PCA space. Additionally, we discovered the topics bearing negative tones and warning signs by sentiment analysis. The results flagged up the issues of the topics, Biomedical Related, International Dynamics and Psychological Impact. The findings could serve as a guideline for researchers who explore new research directions and policymakers who need to make decisions about which research projects to support.

• Journal of Distribution Science
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• v.20 no.3
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• pp.59-69
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• 2022

Purpose: The purpose of this study is to provide information for other journals as well as the continuous development of distribution science research by confirming the globalization performance of the Journal of Distribution Science (JDS), the main journal of KODISA. Research Design, Data, and Methodology: A total of 863 papers published in JDS from 2011 to 2021 searched by scienceON were divided into 4 periods and analyzed under the headings of submission system, standardity, collaboration, and degree of achievement of publication goals. SPSS 24.0 and R 4.1.1 package were used to perform the publication frequency analysis, crosstab-analysis, keyword frequency analysis, and LDA topic modeling were performed. In addition, trend analysis with weight applied to each word was performed. Results: It was found that the ratio of English-written papers, which is the indicator of a journal's starndardity, is continuously increasing, and the ratio of overseas authors, which is the indicator of collaboration, is also continuously increasing. It was confirmed through keyword trend analysis by period and LDA topic modeling results - which were weighted to confirm the degree of achievement of the journal's publication goal - that the articles published by the journal has been in agreement with monthly research topic proposed by JDS. Conclusion: By examining the five criteria for globalization, it can be concluded that JDS's efforts for globalization are achieving significant results and providing effective directions for other academic journals. However, in order for JDS to become a top academic journal, it was suggested that efforts should be made to establish a system for collaborative research by domestic and foreign authors, as well as to provide a clear definition for the monthly research topics and classification of sub-topics.