• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.340-342
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• 2022

Index Terms, or keywords, are an important component of research papers because they present a quick overview of the main subjects covered in the research paper by highlighting the most important nouns. In this study, we extracted the author-assigned index terms from KIICE Conference Proceedings dating back to 2018 for seasonal conferences, and 2016 for the international conference (ICFICE). The extracted index terms were standardized and analyzed to gain an understanding of research topic trends and any over or under-represented research topics. This kind of index term analysis is expected to be useful in helping researchers not only identify additional potential topics for their own research, but also aid them in selecting from a common vocabulary of keywords when they assign index terms to their research papers.

• Smart Media Journal
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• v.11 no.10
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• pp.54-64
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• 2022

A big data-driven digital transformation is defined as a process that aims to innovate companies by triggering significant changes to their capabilities and designs through the use of big data and various technologies. For a successful big data-driven digital transformation, reviewing related literature, which enhances the understanding of research statuses and the identification of key research topics and relationships among key topics, is necessary. However, understanding and describing literature is challenging, considering its volume and variety. Establishing a common ground for central concepts is essential for science. To clarify key research topics on the big data-driven digital transformation, we carry out a comprehensive literature review by performing text mining of 439 articles. Text mining is applied to learn and identify specific topics, and the suggested key references are manually reviewed to develop a state-of-the-art overview. A total of 10 key research topics and relationships among the topics are identified. This study contributes to clarifying a systematized view of dispersed studies on big data-driven digital transformation across multiple disciplines and encourages further academic discussions and industrial transformation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.170-185
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• 2023

The advent of big data has brought about the need for analytics. Natural language processing (NLP), a field of big data, has received a lot of attention. Topic modeling among NLP is widely applied to identify key topics in various academic journals. The Korean Society of Industrial and Systems Engineering (KSIE) has published academic journals since 1978. To enhance its status, it is imperative to recognize the diversity of research domains. We have already discovered eight major research topics for papers published by KSIE from 1978 to 1999. As a follow-up study, we aim to identify major topics of research papers published in KSIE from 2000 to 2022. We performed topic modeling on 1,742 research papers during this period by using LDA and BERTopic which has recently attracted attention. BERTopic outperformed LDA by providing a set of coherent topic keywords that can effectively distinguish 36 topics found out this study. In terms of visualization techniques, pyLDAvis presented better two-dimensional scatter plots for the intertopic distance map than BERTopic. However, BERTopic provided much more diverse visualization methods to explore the relevance of 36 topics. BERTopic was also able to classify hot and cold topics by presenting 'topic over time' graphs that can identify topic trends over time.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.3
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• pp.273-289
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• 2019

The goal of this study is to analyze topics discussed in academic papers on multiculture in Korea to figure out research trends in the field. In order to do topic analysis, LDA (Latent Dirichlet Allocation)-based topic modeling methods are employed. Through the analysis, it is possible to track topic changes in the field and it is found that topics related to 'social integration' and 'multicultural education in schools' are hot topics, and topics related to 'cultural identity and nationalism' are cold topics among top five topics in the field.

• East Asian Journal of Business Economics (EAJBE)
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• v.11 no.1
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• pp.53-71
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• 2023

Purpose - This study aims to find clues necessary for the direction of leadership development suitable for the current situation by exploring the direction in which leadership has been studied from the perspective of domestic researchers, along with the arrangement of leadership theories studied in various ways. Research design, data, and methodology - A total of 7,425 papers were obtained due to the search, and 5,810 papers with English abstracts were used for analysis. For analysis, word frequency analysis, word clouding, and co-occurrence were confirmed using Python 3.7. In addition, after classifying topics related to research trends through BERTopic and LDA, trends were identified through dynamic topic modeling and OLS regression analysis. Result - As a result of the BERTopic, 14 topics such as 'Leadership management and performance' and 'Sports leadership' were derived. As a result of conducting LDA on 1,976 outliers, five topics were derived. As a result of trend analysis on topics by year, it was confirmed that five topics, such as 'military police leadership' received relative attention. Conclusion - Through the results of this study, a study on the reinterpretation of past leadership studies, a study on LMX with an expanded perspective, and a study on integrated leadership sub-factors of modern leadership theory were proposed.

• Journal of the Korean School Mathematics Society
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• v.24 no.4
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• pp.349-367
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• 2021

In this study, 85 studies on probability education from 2000 to 2020 were analyzed by publishing year, journals, research subjects, and research topics. Especially, fundamental probabilistic ideas presented by Batanero et al.(2016) were applied to examine which topics were dominant in domestic probability education research. As a result, it was found that there has been a few research in probability education in Korea during the past 20 years, and the number of human subject studies was slightly more than the number of non-human subject studies. In addition, the analysis of research topics according to the fundamental probabilistic ideas showed that two topics, conditional probability and independence and combinatorial enumeration and counting, were dominant in domestic probability education research. However, while both conditional probability and independence and combinatorial enumeration and counting are introduced to young children using intuitive manners in international probability education research, subjects related to these topics were primarily high school students and pre and in-service teachers. Based on the results of this study, the implications for the goal and the direction of future probability education research were discussed.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.188-192
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• 2007

This paper presents a current perspective on advanced fusion research trends in the construction industry as reflected in the proceedings of International Symposium on Automation and Robotics in Construction (ISARC) which has focused on advanced fusion technology in last decades. The paper reports the results of a 7-year analysis of papers between 2000 and 2006. The analysis focused on such data as research topics of the proceedings. The paper summarizes the data extracted from the paper and uses it to analyze advanced fusion research trends. The research result shows that the top research topics in advanced fusion research areas are construction robots and automation and intelligent construction management. The research also found that research related to advanced fusion technology is increasing throughout the world and topics are changing as current needs change.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.3
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• pp.71-96
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• 2023

This study aimed to investigate key research areas in the field of Library and Information Science (LIS) by analyzing trends and identifying emerging topics. To facilitate the research, a collection of 40,897 author keywords from 11,252 papers published in the past 30 years (1993-2022) in five journals was gathered. In addition, keyword analysis, as well as Principal Component Analysis (PCA) and correlation analysis were conducted, utilizing variables such as the number of articles, number of authors, ratio of co-authored papers, and cited counts. The findings of the study suggest that two topics are likely to develop as promising research areas in LIS in the future: machine learning/algorithm and research impact. Furthermore, it is anticipated that future research will focus on topics such as social media and big data, natural language processing, research trends, and research assessment, as they are expected to emerge as prominent areas of study.

• Korean Medical Education Review
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• v.20 no.2
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• pp.91-102
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• 2018

This study explored medical students' major research topics and research methods by analyzing 184 academic articles pertaining to the characteristics of medical students from 2007 to 2017. Results showed many papers dealing with medical students' emotional and cognitive aspects, student counseling, clinical practice education, and curriculum management. According to the medical education accreditation board, research trends were found mostly in the student and curriculum areas of learner characteristics, medical humanities, student counseling, clinical practice education, and curriculum management. Common research topics have been steadily increasing since the introduction of the evaluation accreditation standard in 2012. Medical students predominantly used quantitative research methods for the studies. In the future, it is necessary to ensure that research topics such as CQI, digital- and performance-based clinical practice, and convergent curriculum within the Fourth Industrial Revolution are being studied. In addition, it is crucial to investigate learners' unique, dynamic, and qualitative characteristics through qualitative and mixed methods.

• The Journal of Information Systems
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• v.33 no.2
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• pp.81-103
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• 2024

Purpose The purposes of the study are to explore the overall theories used in e-commerce adoption research for small enterprises, to demonstrate the research topics and the growth of the research topics in e-commerce adoption for small businesses over twenty years by co-word analysis and to suggest future directions on e-commerce adoption research in small enterprises. Design/methodology/approach This study used bibliometrics approach to systematically review electronic commerce adoption in small enterprises. More specifically, the study used co-citation to reveal the structure and theoretical foundations and keyword network analysis to understand the changes of research themes in small business e-commerce adoption research from 1999 to 2023. Findings According to the bibliometrics analysis result, this study revealed the nine research topics in small enterprise e-commerce adoption. In addition, this study can be applied to start e-commerce adoption research on small enterprises with a theoretical framework.