• 한국정보시스템학회지:정보시스템연구
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• 제33권2호
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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.

• 지질공학
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• 제34권3호
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• pp.429-445
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• 2024

국내 지질공학 분야를 대표하는 학술지인 "지질공학"은 1991년에 창간되어 현재까지 지속적으로 학술 활동 및 다양한 연구 논문을 발표하고 있다. 지난 수십 년 동안 많은 연구자들이 특정 분야를 주제로 한 문헌 고찰 연구를 수행해 왔으나, 학술지 "지질공학"을 대상으로 수행한 문헌고찰 연구는 미비한 실정이다. 따라서, 본 연구에서는 텍스트 마이닝 기법 중 하나인 잠재 디리클레 할당(latent Dirichlet allocation, LDA) 모델을 적용하여 연구 주제 분류 및 연구동향을 분석하였으며, 네트워크 분석을 통해 시대별 주제 간의 연관성을 파악하였다. 분석 결과 총 7개의 연구 주제로 분류되었으며, 3가지 연구동향(Classic topic, Emerging topic, Stable topic)으로 나누어 해석하였다. Classic topic에는 "지구물리학"과 "구조지질학"으로 분석되었으며, 초기에는 주요 논의 주제였으나 시간이 지남에 따라 연구 비중이 감소하였다. Emerging topic은 최근 연구가 활발한 "수리지질학"과 "지질재해"로 분석되었으며, 'Stable topic'은 지속적으로 연구 비중이 유지된 "지반 구조물", "지반 역학", "환경지질학"으로 나타났다. 네트워크 분석 결과, 2008년 이전에는 "구조지질학"이 중심 주제였으나, 2008년 이후 "지반 구조물"분야로 중심 주제가 이동하며 연구의 초점이 변화하였다. 본 연구는 학술지 "지질공학"의 연구 흐름과 발전 과정을 이해하고, 향후 연구 방향을 설정하는 데 중요한 자료를 제공하였음에 의의가 있다.

• 임상간호연구
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• 제17권3호
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• pp.307-318
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• 2011

Purpose: This study was to identify topics for evidence-based clinical nursing practice guidelines in Korea. Methods: Data were collected from 330 staff nurses from 10 general hospitals and 53 nurses in charge of nursing education in 110 hospitals with over 500 beds. Using open questions, the nurses identified activities which could not be verified, which lacked consistency among nurses, clinical units and/or hospitals, which were not based on the up-to-date knowledge and which needed reform. The data were analysed by content analysis using a qualitative methodology. Results: Collected data consisted of 1882 clinical topics, which were classified into 50 topics, 207 mid-categories, and 456 sub-categories. The most frequent topics in order of frequency were medications, central line management, intravenous injections, urinary catheterization, perioperative nursing care, skin tests, pressure ulcer care, blood transfusions, laboratory examination-culture, respiratory care which were performed routinely in clinical setting by staff nurses. Conclusion: The research findings indicate the urgent need to develop evidence-based clinical nursing practice guidelines related to these research findings. Further research is needed to identify topics related to health promotion, and symptom/management of health problem.

• 한국컴퓨터정보학회논문지
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• 제28권10호
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• pp.55-65
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• 2023

본 논문에서는 딥러닝 및 강화학습 연구에 대해 KeyBERT(Keyword extraction with Bidirectional Encoder Representations of Transformers) 알고리즘 기반의 토픽 추출 및 토픽 출현 빈도 분석으로 급변하는 딥러닝 관련 연구 동향 분석을 파악하고자 한다. 딥러닝 알고리즘과 강화학습에 대한 논문초록을 크롤링하여 전반기와 후반기로 나누고, 전처리를 진행한 후 KeyBERT를 사용해 토픽을 추출한다. 그 후 토픽 출현 빈도로 동향 변화에 대해 분석한다. 분석된 알고리즘 모두 전반기와 후반기에 대한 뚜렷한 동향 변화가 나타났으며, 전반기에 비해 후반기에 들어 어느 주제에 대한 연구가 활발한지 확인할 수 있었다. 이는 KeyBERT를 활용한 토픽 추출 후 출현 빈도 분석으로 연구 동향변화 분석이 가능함을 보였으며, 타 분야의 연구 동향 분석에도 활용 가능할 것으로 예상한다. 또한 딥러닝의 동향을 제공함으로써 향후 딥러닝의 발전 방향에 대한 통찰력을 제공하며, 최근 주목 받는 연구 주제를 알 수 있게 하여 연구 주제 및 방법 선정에 직접적인 도움을 준다.

• 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.

• 한국융합학회논문지
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• 제10권2호
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• pp.75-81
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• 2019

본 연구는 통계적인 기법을 융합 활용하여 국내 갑상선암과 관련된 연구 토픽의 동향 및 변화 추세를 알아보기 위함이다. DBpia에 등록되어 있는 갑상선암 관련 논문을 대상으로 LDA(latent Dirichlet allocation) 기반의 토픽 모형을 적용한 결과, 4개의 연구 토픽을 도출하였으며 각 토픽은 "Surgery", "Disease aggressiveness", "Survival analysis", "Well-being of patients"에 관한 내용으로 확인되었다. 다범주 로짓모형을 이용하여 연구 토픽의 시대적 추이를 확인한 결과, 2000년 이전에는 "Surgery", 2000년대에는 "Disease aggressiveness"와 "Survival analysis", 2010년 이후에는 "Survival analysis"와 특히 "Well-being of patients"에 관한 연구가 많이 이루어졌음을 확인하였다. 이는 향후 갑상선암 연구의 방향 모색에 필요한 기초자료로 활용될 수 있을 것이며, 최근 환자의 복지로 크게 전환된 연구 토픽의 변화가 다른 질병에서도 관찰되는지 추후 검토할 필요가 있다.

• 한국학교보건학회지
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• 제33권3호
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• pp.184-193
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• 2020

Purpose: This study was designed to investigate the trends in school health research in Korea using probabilistic latent semantic analysis. The study longitudinally analyzed the abstracts of the papers published in 「The Journal of the Korean Society of School Health」 over the recent 17 years, which is between 2004 and August 2020. By classifying all the papers according to the topics identified through the analysis, it was possible to see how the distribution of the topics has changed over years. Based on the results, implications for school health research and educational uses of latent semantic analysis were suggested. Methods: This study investigated the research trends by longitudinally analyzing journal abstracts using latent dirichlet allocation (LDA), a type of LSA. The abstracts in 「The Journal of the Korean Society of School Health」 published from 2004 to August 2020 were used for the analysis. Results: A total of 34 latent topics were identified by LDA. Six topics, which were「Adolescent depression and suicide prevention」, 「Students' knowledge, attitudes, & behaviors」, 「Effective self-esteem program through depression interventions」, 「Factors of students' stress」, 「Intervention program to prevent adolescent risky behaviors」, and 「Sex education curriculum, and teacher」were most frequently covered by the journal. Each of them was dealt with in at least 20 papers. The topics related to 「Intervention program to prevent adolescent risky behaviors」, 「Effective self-esteem program through depression interventions」, and 「Preventive vaccination and factors of effective vaccination」 appeared repeatedly over the most recent 5 years. Conclusion: This study introduced an AI-powered analysis method that enables data-centered objective text analysis without human intervention. Based on the results, implications for school health research were presented, and various uses of latent semantic analysis (LSA) in educational research were suggested.

• 융합경영연구
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• 제11권3호
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• pp.47-66
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• 2023

Purpose: The purpose of this study is to identify research trends related to ESG by domestic and overseas researchers so far, and to present research directions and clues for the possibility of applying ESG to Korean companies in the future and ESG practice through comparison of derived topics. Research design, data and methodology: In this study, as of October 20, 2022, after searching for the keyword 'ESG' in 'scienceON', 341 domestic papers with English abstracts and 1,173 overseas papers were extracted. For analysis, word frequency analysis, word co-occurrence frequency analysis, BERTopic, LDA, and OLS regression analysis were performed to confirm trends for each topic using Python 3.7. Results: As a result of word frequency analysis, It was found that words such as management, company, performance, and value were commonly used in both domestic and overseas papers. In domestic papers, words such as activity and responsibility, and in overseas papers, words such as sustainability, impact, and development were included in the top 20 words. As a result of analyzing the co-occurrence frequency of words, it was confirmed that domestic papers were related mainly to words such as company, management, and activity, and overseas papers were related to words such as investment, sustainability, and performance. As a result of topic modeling, 3 topics such as named ESG from the corporate perspective were derived for domestic papers, and a total of 7 topics such as named sustainable investment for overseas papers were derived. As a result of the annual trend analysis, each topic did not show a relatively increasing or decreasing tendency, confirming that all topics were neutral. Conclusions: The results of this study confirmed that although it is desirable that domestic papers have recently started research on consumers, the subject diversity is lower than that of overseas papers. Therefore, it is suggested that future research needs to approach various topics such as forecasting future risks related to ESG and corporate evaluation methods.

• 한국콘텐츠학회논문지
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• 제16권4호
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• pp.36-44
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• 2016

우리나라의 한정된 예산과 연구자원을 활용하여 뇌과학 분야 연구성과를 극대화하기 위해서는 뇌연구 분야 중 강점을 가질 수 있는 융합연구 분야를 선정하여 우선적으로 육성할 필요가 있다. 본 연구에서는 선도가능성, 혁신성, 기대성과 등을 바탕으로 중점 연구분야의 우선순위를 결정함으로써 뇌과학 정책 결정에 가이드라인을 제공하고자 한다. 이를 위해 우선 뇌과학 분야 국내 리더급 연구자들에게 뇌과학 중점 연구분야 후보로 5개 영역, 즉 신경교세포, 뇌정밀의학, 신경후성유전학, 뇌신경모사컴퓨터, 뇌파이용 대상 구동기술을 추천받았다. 그 다음 AHP를 통해 중점후보 분야와 평가항목 간의 상대적 가중치를 결정하고 그 우선순위를 결정하였다. 평가 항목 중 선도가능성 등의 세부항목이 포함된 유망도가 중점분야 선정에 있어 가장 중요한 평가 요소인 것으로 나타났으며, 이러한 평가 요소로 비교 분석해본 결과 중점 연구분야 후보 중에 신경교세포의 가중치가 가장 높은 것으로 나타나 관련 정책 추진시 가장 우선적으로 고려해야 할 것으로 판단된다.

• 한국임상약학회지
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• 제29권3호
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• pp.173-185
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• 2019

Objective: To gather inputs from clinical experts on selecting and prioritizing research topics, to address unmet vaccine safety needs. Methods: A questionnaire containing 15 vaccine safety assessment research proposals was sent to 28 vaccine experts chosen from various domestic medical association boards, and the rationale for each of the proposals was provided by presenting the following information: 1) a brief summary of the clinical safety studies on the vaccine, conducted by the Clinical Immunization Safety Assessment (CISA) project group, supervised by the United States Center for Disease Control (U.S. CDC), and 2) a summary of recently published studies that address vaccine safety issues. The experts were instructed to select and rank 5 topics in the order of preference, and the preference score for each proposed topic was calculated by assigning points on a scale of 1 to 5. Results: All 28 experts responded to the questionnaire, and the following topics were selected according to their calculated preference scores: 1) Human papillomavirus vaccine safety profile in the Korean female adolescents; 2) A signal detection of adverse events following Influenza vaccination: comparison between the US and South Korea; 3) Incidence of anaphylaxis following National Immunization Program vaccines between 2008 and 2017; 4) Safety of quadrivalent influenza vaccines compared to trivalent influenza vaccines; and 5) Pneumococcal vaccine safety profile in the general population. Conclusion: Five research topics addressing vaccine safety were selected, for which well-constructed research protocols need to be promptly developed to address current unmet vaccine safety needs in South Korea.