• The Mathematical Education
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• v.59 no.3
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• pp.201-216
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• 2020

This study analyzed 493 domestic mathematics curriculum articles published in KCI's listings from 1997 to 2019 using LDA topic modeling. As a result, domestic mathematics curriculum research could be categorized into eight topics such as 'context in a curriculum', 'analysis a curriculum by the mathematical concept', 'form, system, meaning, and character of a curriculum', 'instruction and application of a curriculum', 'implementation and evaluation of a curriculum', 'tasks in a curriculum', 'analysis of a curriculum based on ability', 'compare and analysis curriculum and textbook'. The topic 'implementation and evaluation of a curriculum' was identified with the lowest proportion. Also, we performed the simple regression analysis with the weight of topics in the application period of the curriculum, and 'analysis of a curriculum based on ability' appeared as a 'hot topic'. Furthermore, topics appeared differently depending on the application period of the curriculum. Some of the appeared topics showed a tendency to match the emphasis of the highlight in a mathematics curriculum. Based on the results, future studies should develop frameworks for mathematics curriculum studies and extend the field of mathematical curriculum studies to make progress. Furthermore, future studies are needed to examine the enactment, feedback, and competency evaluation in the mathematical curriculum.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.4
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• pp.91-111
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• 2023

This study aims to analyze research topics within the domain of archival studies by examining bibliographic information from academic papers in archival science, library and information science, and history. After collecting 1,173 academic papers, network analysis was performed based on author keyword data, topic modeling was conducted from abstract data, and the analysis results were organized over time. The network analysis results based on author keywords confirmed that the research topic network actively changed according to variations in major laws and policies. Moreover, topic modeling from the abstract showed that the subjects of the entire academic paper were divided into "Records Management," "Archiving," and "National Records Policy." Notably, from 2002 to 2009, "Records Management" and "National Records Policy" were relatively dominant, but it has achieved balanced quantitative growth since 2009, peaking in 2019.

• Asian Journal for Public Opinion Research
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• v.7 no.3
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• pp.169-198
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• 2019

This study focused on the increase in refugee-related discourse in Korean society with the recent inflow of asylum seekers to Jeju Island. The purpose of our study was to understand the trends in public opinion concerning the acceptance of refugees by analyzing the content of refugee-related video commentary on YouTube. Topic modeling was conducted to analyze the main points, context, and ideas in the comments. The results indicated that the media mainly focus on the pros and cons of refugees, restricting the refugee issue to the problem of acceptance with a narrow focus on the case of Jeju Island. Refugee acceptance was treated as overwhelmingly unacceptable in the comments. We found that commenters often used negative discourse in the comments as a device for reproducing and amplifying hate speech.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.31 no.4
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• pp.19-27
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• 2023

In this study, a total of 2,584 domestic research papers with the keywords "Aviation Safety" and "Aviation Accidents" were subjected to Text Mining analysis. Various text mining techniques, including keyword frequency analysis, word correlation analysis, network analysis, and topic modeling, were applied to examine the research trends in the field of aviation safety. The results revealed a significant increase in research using the keyword "Aviation Safety" since 2015, with over 300 papers published annually. Through keyword frequency analysis, it was observed that "Aircraft" was the most frequently mentioned term, followed by "Drones" and "Unmanned Aircraft." Phi coefficients were calculated for words closely related to "Aircraft," "Aviation," "Drones," and "Safety." Furthermore, topic modeling was employed to identify 12 distinct topics in the field of aviation safety and aviation accidents, allowing for an in-depth exploration of research trends.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.47-56
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• 2021

The purpose of this study is to use network analysis to identify trends in university personality-related studies and provide implications for future research directions. For the purpose of this study, 194 papers related to personality of university students published in Korean scholarly journals. First, research began to be published in 2004, slightly increased in 2012, continued an upward curve from 2015, peaked in 2017, and is confirmed to be a downward trend. Second, the main keywords with the centrality analysis were 'society' and 'cultivation'. Third, keywords on the cognitive side and individual dimension of personality in the first period (2004 - 2010), social dimension and emotional side of personality in the second period (2011-2015), and social level and cognitive, emotional, and behavioral aspects of personality in the third period (2016-2020). Fourth, Topic 2 consisted of keywords of ability, life, interpersonal, satisfaction, and adaptation, and Topic 1 consisted of competence, morality, citizens, society, and practice. Fifth, Topic 4 alone in the first period, in the order of Topic 1 and Topic 2 in the second period, and in the order of Topic 2 and Topic 1 in the third period.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.95-106
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• 2021

The purpose of this study is to derive major topics in content R&D and provide directions for academic development by exploring research trends over the past 20 years using topic modeling targeting 9,858 papers published in the Journal of the Korean Contents Association. To secure the reliability and validity of the extracted topics, not only the quantitative evaluation technique but also the qualitative technique were applied step-by-step and repeated until a corpus of the level agreed upon by the researchers was generated, and detailed analysis procedures were presented accordingly. As a result of the analysis, 8 core topics were extracted. This shows that the Korean Contents Association is publishing convergence and complex research papers in various fields without limiting to a specific academic field. Also, before 2012, the proportion of topics in the field of engineering and technology appeared relatively high, while after 2012, the proportion of topics in the field of social sciences appeared relatively high. Specifically, the topic of 'social welfare' showed a fourfold increase in the second half compared to the first half. Through topic-specific trend analysis, we focused on the turning point in time at which the inflection point of the trend line appeared, explored the external variables that affected the research trend of the topic, and identified the relationship between the topic and the external variable. It is hoped that the results of this study can provide implications for active discussions in domestic content-related R&D and industrial fields.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.74-86
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• 2019

As many existing research fields are matured academically, researchers have encountered numbers of academic, social and other problems that cannot be addressed by internal knowledge and methodologies of existing disciplines. Earlier, pioneers of researchers thus are following a new paradigm that breaks the boundaries between the prior disciplines, fuses them and seeks new approaches. Moreover, developed countries including Korea are actively supporting and fostering the convergence research at the national level. Nevertheless, there is insufficient research to analyze convergence trends in national R&D support projects and what kind of content the projects mainly deal with. This study, therefore, collected and preprocessed the research proposal data of National Research Foundation of Korea, transforming the proposal documents to term-frequency matrices. Based on the matrices, this study derived detailed research topics through Latent Dirichlet Allocation, a kind of topic modeling algorithm. Next, this study identified the research topics each proposal mainly deals with, visualized the convergence relationships, and quantitatively analyze them. Specifically, this study analyzed the centralities of the detailed research topics to derive clues about the convergence of the near future, in addition to visualizing the convergence relationship and analyzing time-varying number of research proposals per each topic. The results of this study can provide specific insights on the research direction to researchers and monitor domestic convergence R&D trends by year.

• Journal of KIISE
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• v.44 no.11
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• pp.1138-1148
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• 2017

Topic extraction is a technology that automatically extracts a set of topics from a set of documents, and this has been a major research topic in the area of natural language processing. Representative topic extraction methods include Latent Dirichlet Allocation (LDA) and word clustering-based methods. However, there are problems with these methods, such as repeated topics and mixed topics. The problem of repeated topics is one in which a specific topic is extracted as several topics, while the problem of mixed topic is one in which several topics are mixed in a single extracted topic. To solve these problems, this study proposes a method to extract topics using an LDA that is robust against the problem of repeated topic, going through the steps of separating and merging the topics using the similarity between words to correct the extracted topics. As a result of the experiment, the proposed method showed better performance than the conventional LDA method.

• Journal of Science Education
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• v.42 no.3
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• pp.371-389
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• 2018

This study focuses on the fact that students and teachers commonly have difficulty in 'selecting the topic' in many activities including student-led research that is conducted from topic selection to the drawing of conclusion. The purpose of this study is to develop a manual for science teaching research. The instructional manuals of 4 stages were developed based on practical knowledge that can be implemented in the actual class through previous research and literature. Each stage is composed of , , , and . In the third stage, students are expected to find scientific questions and develop them into research topics through detailed class research on newspaper articles, scientific magazines, traditional knowledge, proverbs, daily life, and textbook experiments. In the experimental group, the final research topic was selected through a variety of sources such as textbook experiments, proverbs, YouTube images, newspaper articles, individual WHY NOTEs, and understood the conditions of the scientific research topic and expressed the variables in the research title. However, in the control group, some students did not consider the research scope of the selected research subjects to be specific or not to be able to study at their level. As a result of giving the students as much autonomy as possible, many groups did not fully understand the previous research and submitted it. Based on the results of this study, it can be concluded that development and use of a 'topic selection stage' centered practice manual for general high school teachers would not only improve the students' abilities to discover solutions to scientific questions, but it will also help shift their attitudes towards science in a positive direction.

• The Journal of Information Systems
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• v.18 no.2
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• pp.35-59
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• 2009

The study of Information Systems(IS) is a relatively new discipline area, thus an analysis of the latest research literature could be useful to identify what the researchers are doing and what can be done to improve our discipline. With that purpose in mind, this study analyzes the total 208 articles published in "The Journal of Information Systems~ between 2001 and 2008. The classification system that comprises three key characteristics of diversity (research topic, research method, and reference discipline) was developed based on a review of prior literature. The results of this study were also compared with Kim et al.(2005)'s and Vessey et al.(2002)'s results to identify issues in current Information Systems research and 10 suggest some recommendations for future In formation Systems research. The findings identify popular research topic:s, the dominant research method, and reference discipline. The popular research topics consists of organizational concepts, problem domain-specific concepts, and systems/software management concepts. Field study was characterized as the dominant research method in the papers included in the study. Information Systems itself represents the major theoretical reference of the studies. However, many papers in this study relied on a number of reference disciplines., none of which was dominant, or they did not rely on a specific reference discipline. Finally, this study suggests more research on the disciplinary issues, more training on the research method, more accurate and specific reference discipline, and controlled diversity.