• 농촌계획
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• 제29권4호
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• pp.81-92
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• 2023

The purpose of this study is to identify rural research topics, differences in research topics over time, and key mediators through the analysis of academic research trends using topic modeling. This study analyzed a total of 1,183 articles published in the Journal of Rural Planning and Rural Society over a 23-year period (2000-2022). We categorized rural research topics into 30, examined the proportion of research in each topic, and identified major changes in research topics over time. We also identified key words that mediate between research topics. The study found that, first, rural research trends can be categorized into five types (resources and utilization, area/space, people, ecosystem/environment, and tourism), with area/space being the most studied. Subtopics include rural amenities, rural disappearance/village miniaturization, and rural landscape management. Second, the research topics for each period were different. In the first period(2003-2007), the main research topics were rural amenities and Agricultural production- based climate vulnerability assessment. In the second period(2008-2012), the main research topics were Rural extinction and village depopulation, and rural landscape management, and in the third period(2013-2017), the main research topics were rural sixth industrialization and rural ecotourism. In the fourth period(2018-2022), rural development planning and rural life services(life SOC) were the main research topics. The significance of this study is that it extends the existing method of analyzing research trends and provides basic data to enhance comprehensive insights and understanding of rural research.

• Journal of Information Science Theory and Practice
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• 제6권4호
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• pp.39-53
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• 2018

While the body of research on metadata has grown substantially, there has been a lack of systematic analysis of the field of metadata. In this study, we attempt to fill this gap by examining metadata literature spanning the past 20 years. With the combination of a text mining technique, topic modeling, and network analysis, we analyzed 2,713 scholarly papers on metadata published between 1995 and 2014 and identified main topics and trends in metadata research. As the result of topic modeling, 20 topics were discovered and, among those, the most prominent topics were reviewed in detail. In addition, the changes over time in the topic composition, in terms of both the relative topic proportions and the structure of topic networks, were traced to find past and emerging trends in research. The results show that a number of core themes in metadata research have been established over the past decades and the field has advanced, embracing and responding to the dynamic changes in information environments as well as new developments in the professional field.

• Smart Structures and Systems
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• 제29권2호
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• pp.361-374
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• 2022

As civil infrastructure has continued to age worldwide, its structural integrity has been threatened owing to material deteriorations and continual loadings from the external environment. Structural Health Monitoring (SHM) has emerged as a cost-efficient method for ensuring structural safety and durability. As SHM research has gradually addressed an increasing number of structure-related problems, it has become difficult to understand the changing research topic trends. Although previous review papers have analyzed research trends on specific SHM topics, these studies have faced challenges in providing (1) consistent insights regarding macroscopic SHM research trends, (2) empirical evidence for research topic changes in overall SHM fields, and (3) methodological validations for the insights. To overcome these challenges, this study proposes a framework tailored to capturing the trends of research topics in SHM through a bibliometric and network analysis. The framework is applied to track SHM research topics over 15 years by identifying both quantitative and relational changes in the author keywords provided from representative SHM journals. The results of this study confirm that overall SHM research has become diversified and multi-disciplinary. Especially, the rapidly growing research topics are tightly related to applying machine learning and computer vision techniques to solve SHM-related issues. In addition, the research topic network indicates that damage detection and vibration control have been both steadily and actively studied in SHM research.

• 지적과 국토정보
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• 제48권1호
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• pp.15-33
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• 2018

본 연구의 주된 목적은 LDA를 이용하여 국제지적연구의 주제와 연구추세를 확인하는 것이었다. 이러한 연구목적을 달성하기 위해 나는 LDA와 국제지적연구에 관한 선행연구를 검토하였고 이를 기반으로 4 개의 연구 질문을 설정하였다. 이러한 연구 질문에 답을 구하기 위해 나는 FIG Peer Review Journal에 2008년 1월1일 부터 2017년 10월 31일 사이에 발표된 370편의 논문들을 LDA를 이용하여 분석하였다. 분석의 결과 나는 국제지적연구에 12개의 주요 주제가 존재하고 있음을 확인하였다. 그리고 이러한 주제 중에 가장 영향력 있는 주제는 topic 2 (지적정보시스템)로 확인되었으며 또한 topic 5 (토지개발과 토지행정)도 전체 문서에서 중요한 역할을 수행하고 있는 주제로 파악되었다. 이두 주제는 지난 10년 동안 추세선이 매우 활발하게 움직인 가장 인기 있는 주제들로서 앞으로의 지적연구에서도 주도적인 역할을 수행할 것이 틀림없다.

• 한국수학교육학회지시리즈D:수학교육연구
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• 제24권4호
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• pp.313-335
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• 2021

The purpose of this research is to identify topics discussed by Korean mathematics education studies and examine research trends for 15 years. I applied latent Dirichlet allocation (LDA) to the original text datasets including English abstracts of 3,157 articles published in eight journals indexed by the Korean Citation Index (KCI) from 1997 to 2019. I identified an LDA model with 60 topics, then research trends in 2,884 articles between 2002 and 2018 were as follows; mathematics educators have paid most attention to teacher education through 2010 to 2015 and curriculum analysis after 2016. The findings in this research can contribute to understand what have been discussed in Korean mathematics education society as well as what will and need to be emphasized more in the future compared to the global research trends. In addition, LDA has potentials to identify topics and keywords of manuscripts newly written and submitted to any journals in addition to information provided by authors.

• 무역학회지
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• 제45권3호
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• pp.55-69
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• 2020

This study examines the research trends and knowledge structure of international trade studies using topic modeling method, which is one of the main methodologies of text mining. We collected and analyzed English abstracts of 1,868 papers of three Korean major journals in the area of international trade from 2003 to 2019. We used the Latent Dirichlet Allocation(LDA), an unsupervised machine learning algorithm to extract the latent topics from the large quantity of research abstracts. 20 topics are identified without any prior human judgement. The topics reveal topographical maps of research in international trade and are representative and meaningful in the sense that most of them correspond to previously established sub-topics in trade studies. Then we conducted a regression analysis on the document-topic distributions generated by LDA to identify hot and cold topics. We discovered 2 hot topics(internationalization capacity and performance of export companies, economic effect of trade) and 2 cold topics(exchange rate and current account, trade finance). Trade studies are characterized as a interdisciplinary study of three agendas(i.e. international economy, International Business, trade practice), and 20 topics identified can be grouped into these 3 agendas. From the estimated results of the study, we find that the Korean government's active pursuit of FTA and consequent necessity of capacity building in Korean export firms lie behind the popularity of topic selection by the Korean researchers in the area of int'l trade.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2007년도 정기 학술대회 논문집
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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.

• 의학교육논단
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• 제20권2호
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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.

• 한국응급구조학회지
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• 제26권2호
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• pp.19-35
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• 2022

Purpose: This study aimed to identify research topics in the emergency medical technician (EMT) field and examine research trends. Methods: In this study, 261 research papers published between January 2000 and May 2022 were collected, and EMT research topics and trends were analyzed using topic modeling techniques. This study used a text mining technique and was conducted using data collection flow, keyword preprocessing, and analysis. Keyword preprocessing and data analysis were done with the RStudio Version 4.0.0 program. Results: Keywords were derived through topic modeling analysis, and eight topics were ultimately identified: patient treatment, various roles, the performance of duties, cardiopulmonary resuscitation, triage systems, job stress, disaster management, and education programs. Conclusion: Based on the research results, it is believed that a study on the development and application of education programs that can successfully increase the emergency care capabilities of EMTs is needed.

• Journal of Information Science Theory and Practice
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• 제9권2호
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• pp.47-65
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• 2021

This study aims to identify specific topics, trends, and structural characteristics of scholarly communication research, based on 1,435 articles published from 1970 to 2018 in the Scopus database through Latent Dirichlet Allocation topic modeling, serial analysis, and network analysis. Topic modeling, time series analysis, and network analysis were used to analyze specific topics, trends, and structures, respectively. The results were summarized into three sets as follows. First, the specific topics of scholarly communication research were nineteen in number, including research resource management and research data, and their research proportion is even. Second, as a result of the time series analysis, there are three upward trending topics: Topic 6: Open Access Publishing, Topic 7: Green Open Access, Topic 19: Informal Communication, and two downward trending topics: Topic 11: Researcher Network and Topic 12: Electronic Journal. Third, the network analysis results indicated that high mean profile association topics were related to the institution, and topics with high triangle betweenness centrality, such as Topic 14: Research Resource Management, shared the citation context. Also, through cluster analysis using parallel nearest neighbor clustering, six clusters connected with different concepts were identified.