21세기는 급격한 기후변화와 생물다양성의 위기, 반복되는 전지구적 팬데믹으로 인간과 자연의 관계가 생태적으로 고찰되어야 한다는 사회‧ 문화적 요구와 학문적 필요성이 제기되고 있다. 이에 본 논문은 20세기 초에 시작된 한국의 생태연구를 인간을 둘러싼 자연과 생태환경에 주목 하고 그 경향성과 특성을 같은 시기에 간행된 학술지 『트랜잭션』의 주요 논문을 통해 고찰했다. 개항 이후 근대적 자연탐사는 서구를 중심으로 시작되었고 1900년 영국 왕립아시아학회 한국지부가 설립되면서 전문성 을 갖춘 학회 회원들을 통해 한국의 토착정보와 현장연구가 반영된 생태 연구가 시작되었다. 본 연구는 『트랜잭션』에 수록된 1930-1940년대 자 연 및 생태연구를 체계적으로 정리하고 이를 통해 근대 한국 생태연구가 서구적 자연 조사와 한국의 자생정보 및 토착지식의 교차점에서 형성되 었음을 밝혔다. 또한 한국의 생태연구가 『트랜잭션』이라는 국제적 학술 시스템을 통해 한국의 자연과 생태환경에 대한 근대적 지식의 생성과 유 포가 이루어졌음을 검토하고 그에 대한 기초자료를 제시하였다.

This study analyzes research trends in mushrooms using social network analysis (SNA) and Word2Vec analysis based on 654 papers published in the journal of mushrooms. By tracking changes in research trends through centrality indices of key keywords and temporal keyword associations, it was found that in the early period (2011–2015), research primarily focused on optimizing growth conditions. During the mid-period (2016–2020), studies on strain characteristics and disease resistance became more prominent. In the recent period (2021–2024), research on molecular biology and functional components has expanded significantly, with molecular biology research, substrate and cultivation environment studies, and quality and functional food research emerging as new research areas. Meanwhile, research on Pleurotus ostreatus has been the most active, whereas studies on other mushroom species remain relatively limited, indicating the need for a broader scope in future research. This study provides an in-depth review of the research trends and transformations in the journal of mushrooms, contributing to the discussion on its balanced development and future research directions.

Purpose: This study aimed to analyze the reviewers’ evaluations of papers submitted to the Journal of the Korean Society for Simulation in Nursing between 2019 and June 2024. Methods: We analyzed 117 quantitative (69 published and 48 unpublished) and 16 qualitative (11 published and five unpublished) studies. The reviewers’ checklist-based evaluations were analyzed using means and standard deviations. The scope method was used to examine the reviewers’ subjective evaluations. Results: For quantitative studies, the highest average score among published papers was in the “Research Theme” category (3.64±0.73). Contrastingly, the lowest average scores were in the “Discussion” category, with 3.32±0.74 for quantitative studies and 3.23±0.74 for qualitative studies. In rejected papers, the “Discussion” category recorded the lowest scores, at 2.35±0.74 for quantitative studies and 1.92±0.76 for qualitative studies. Conclusion: The results demonstrated the research characteristics of this journal and focus of the review by providing information on the reviewers’ evaluations. Structured scientific research based on these results will contribute to improving the academic quality of journals by reinforcing the openness and systematicity of academic communication.

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.

This study investigated the trend of research on ‘Food science and Nutrition’ in previously published papers in the Journal of Korean Society of Food Culture (JKSFC) from 2000 to 2021. Total number of published papers in this category in the JKSFC was 693 which we classified into 7 main categories and 40 subcategories. Of these, 256 articles were on ‘experimental cooking’ which was the most studied field among 7 main categories. There was a total of 19 published papers under the category of ‘microbiology and fermentation’. A total of 133 articles were published on ‘functional foods’ and provided essential data for discovering new materials under the theme of various physiological active functions of food materials. Furthermore, 107 articles were included in ‘food processing and storage’, which provided integrated knowledge of economy, stability and practicality based on various technologies. A total of 144 articles was included in the category of ‘nutrition’. Under the category of ‘nutrition’, the most actively studied topic was ‘eating behaviors and dietary habits,’ and the trending topic was ‘use of healthcare big data.’ In conclusion, this review would provide trends of various categories of food science and nutrition area for recent 21 years and suggest directions for future research.

This study examines the trend of research on food and culture in papers published in the Journal of The Korean Society of Food Culture from 1986 to 2020. The journals published a total of 329 papers, which we classified into 5 main categories and 13 middle categories. Of these, 204 articles were on “Korean traditional food culture.” The most studied topic in the entire period was “Perception of Koreans towards traditional food, preference, satisfaction, and usage.” A total of 76 studies related to “Korean contemporary food culture.” The most advanced topic researched concerned “Recognition and attitude”; these studies were consistently carried out throughout the research period. The main classification of “World food culture” encompassed 32 studies, with major research focused on “World's Modern Food Culture” and the most advanced being “Comparison of Food Cultures of Foreign and Korean Food Cultures.” All studies were consistently spaced out during the study period. These studies provide an integrated knowledge in the field of food and culture and can be used as a basic material for related research in the future.

For any research study, in order to achieve the researcher’s intended purpose, the depth of research is added, and the area of the subject is expanded by clearly defining the scope and objective. The study was undertaken to analyze the bibliographic data of 254 papers in the field of foodservice and restaurant published in the Journal of the Korean Society of Food Culture from 2002 to 2021. The study was divided into two periods: 2002 to 2011, and 2012 to 2021. Research topics were derived and research trends according to temporal changes were confirmed through analysis of keyword networks by period. In addition, analyzing the keyword network of simultaneous appearance of “foodservice” and “restaurant”, the research topics were compared and analyzed in relation to which keywords were expanded by period. Our analysis revealed that the research topics were mostly studied for satisfaction and nutrition. Additionally, they were classified into procurement, Korean food before employee menu, marketing, restaurant industry, and quality. In the period from 2002 to 2011, it was confirmed that studies encompassed a wide range of research topics, focusing on foodservice and restaurant; in the second period from 2012 to 2021, the research topics were more classified and subdivided.

Purpose: This study aimed to identify research trends by applying the scoping studies method to articles published from the establishment of the Korean Society for Nursing Simulation in 2011 to June 2021, and to suggest the direction for future research. Method: A total of 73 articles were reviewed by applying the six steps and recommendations for scoping studies as suggested by Arksey and O'Malley. Results: Focusing on the subjects, research topics were classified comprehensively into the experience of nursing students, nurses, professors, and office workers. As a result of analyzing the research process characteristics, practical teaching and learning using simulation technology resources were conducted during most of the research, and a systematic curriculum for learning promotion was devised and applied. Furthermore, nursing performance ability was evaluated, learning situation was identified, and simulation education situation and necessity of clinical field were identified. The keywords “applied technology,” “teaching-learning method,” “environment,” “cognition,” “attitude,” “affect,” “patient status,” “nursing,” and “nursing performance” were identified as eight categories. Conclusion: The post-coronavirus era has provided an opportunity to expand the scope of Korean nursing simulation research, which is going to further contribute to nursing development.

Topic modeling has been receiving much attention in academic disciplines in recent years. Topic modeling is one of the applications in machine learning and natural language processing. It is a statistical modeling procedure to discover topics in the collection of documents. Recently, there have been many attempts to find out topics in diverse fields of academic research. Although the first Department of Industrial Engineering (I.E.) was established in Hanyang university in 1958, Korean Institute of Industrial Engineers (KIIE) which is truly the most academic society was first founded to contribute to research for I.E. and promote industrial techniques in 1974. Korean Society of Industrial and Systems Engineering (KSIE) was established four years later. However, the research topics for KSIE journal have not been deeply examined up until now. Using topic modeling algorithms, we cautiously aim to detect the research topics of KSIE journal for the first half of the society history, from 1978 to 1999. We made use of titles and abstracts in research papers to find out topics in KSIE journal by conducting four algorithms, LSA, HDP, LDA, and LDA Mallet. Topic analysis results obtained by the algorithms were compared. We tried to show the whole procedure of topic analysis in detail for further practical use in future. We employed visualization techniques by using analysis result obtained from LDA. As a result of thorough analysis of topic modeling, eight major research topics were discovered including Production/Logistics/Inventory, Reliability, Quality, Probability/Statistics, Management Engineering/Industry, Engineering Economy, Human Factor/Safety/Computer/Information Technology, and Heuristics/Optimization.