• 제목/요약/키워드: NetMiner4

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간호교육기관의 교육목적 및 교육목표에 대한 토픽 모델링 (Educational goals and objectives of nursing education programs: Topic modeling)

  • 박은준;옥종선;박찬숙
    • 한국간호교육학회지
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    • 제28권4호
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    • pp.400-410
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    • 2022
  • Purpose: This study aimed to understand the keywords and major topics of the educational goals and objectives of nursing educational institutions in South Korea. Methods: From May 10 to May 20, 2022, the educational goals and objectives of all 201 nursing educational institutions in South Korea were collected. Using the NetMiner program, degree and degree centrality, semantic structure, and topic modeling were analyzed. Results: The top keywords and semantic structures of educational goals included 'respect for human (life)-spirit-science-based on, global-competency-professional nurse-nursing personnel-training, professional-science-knowledge-skills, and patients-therapeutic care-relationship.' The educational goals' major topics were clients well-being based on science and respect for human life, a practicing nurse with capabilities and spirit, fostering a nursing personnel with creativity and professionalism, and training of global nurses. The top keywords and semantic structures of the educational objectives included 'holistic care-nursing-research-action-capability, critical thinking-health-problem solving-capability, and efficiency-communication-collaboration-capability.' The educational objectives' major topics were 'nursing professionalism, communication and problem-solving capability; a change of healthcare environments and a progress of nursing practices; fostering professional nurses with creativity and global capability; and clients' health and nursing practice.' Conclusion: Educational goals in nursing presented specific nursing values and concepts, such as respect for human life, therapeutic care relationships, and the promotion of well-being. Educational objectives in nursing presented the competencies of nurses as defined by the Korean Accreditation Board of Nursing Education (KABONE). Recently, the KABONE announced new program outcomes and competencies, which will require the revision of educational goals. To achieve those educational objectives, it is suggested that the expected level of competencies be clearly defined for nursing graduates.

인공지능과 간호에 관한 언론보도 기사의 키워드 네트워크 분석 및 토픽 모델링 (Keyword Network Analysis and Topic Modeling of News Articles Related to Artificial Intelligence and Nursing)

  • 하주영;박효진
    • 대한간호학회지
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    • 제53권1호
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    • pp.55-68
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    • 2023
  • Purpose: The purpose of this study was to identify the main keywords, network properties, and main topics of news articles related to artificial intelligence technology in the field of nursing. Methods: After collecting artificial intelligence-and nursing-related news articles published between January 1, 1991, and July 24, 2022, keywords were extracted via preprocessing. A total of 3,267 articles were searched, and 2,996 were used for the final analysis. Text network analysis and topic modeling were performed using NetMiner 4.4. Results: As a result of analyzing the frequency of appearance, the keywords used most frequently were education, medical robot, telecom, dementia, and the older adults living alone. Keyword network analysis revealed the following results: a density of 0.002, an average degree of 8.79, and an average distance of 2.43; the central keywords identified were 'education,' 'medical robot,' and 'fourth industry.' Five topics were derived from news articles related to artificial intelligence and nursing: 'Artificial intelligence nursing research and development in the health and medical field,' 'Education using artificial intelligence for children and youth care,' 'Nursing robot for older adults care,' 'Community care policy and artificial intelligence,' and 'Smart care technology in an aging society.' Conclusion: The use of artificial intelligence may be helpful among the local community, older adult, children, and adolescents. In particular, health management using artificial intelligence is indispensable now that we are facing a super-aging society. In the future, studies on nursing intervention and development of nursing programs using artificial intelligence should be conducted.

대한가정학회지 연구 동향 및 공저자 네트워크 분석: 2010~2022년 게재 논문을 중심으로 (Research Trends and Co-author Network Analysis of the Journal of the Korean Home Economics Association: Articles Published from 2010 to 2022)

  • 박미정;채정현;한주
    • Human Ecology Research
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    • 제62권1호
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    • pp.15-32
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    • 2024
  • The purpose of this study was to analyze the research trends and co-author networks of academic articles published in the Journal of the Korean Home Economics Association from 2010 to 2022. The network analysis was conducted using Excel and NetMiner 4.4, and the results were as follows. First, the number of published articles has been maintained at around 40 per year since 2019. By field, most articles were published in the field of child studies and family studies, followed by consumer studies, home management, clothing studies, home economics education, food and nutrition, and housing. The research methods were primarily quantitative (71.61%). Second, the most common keywords in the titles of the published articles were "influence" and "relationship", with "influence", "consumer", "mediating effect", "parent", and "control" identified as influential keywords. Third, the published articles were categorized into nine topics based on subject matter, while the number of topic types varied by year. Fourth, the total number of authors of the 627 articles was 712, with 1.92 authors per article, as well as the number of authors who published two or fewer articles accounted for 85.5% of the total. By institution, Yonsei University had the highest number of authors and the highest number of published articles, while Korea National Open University played a leading role in the network of co-authors by institution. This study is significant in providing basic data for the future development of the Korean Home Economics Association and the field of home economics.

동의보감(東醫寶鑑) 두문(頭門) 처방의 네트워크 분석을 통해 간략화한 두부(頭部) 증상의 주요 원인 및 처방 (The Major Causes and Prescriptions for Head Symptoms in Donguibogam Simplified by Network Analysis)

  • 김철현;추홍민;문연주;성강경;이상관
    • 대한한방내과학회지
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    • 제38권6호
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    • pp.1000-1006
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    • 2017
  • Objectives: Head symptoms, such as headache and dizziness, are commonly presented in clinical practice. Although Donguibogam, the representative book of Korean medicine, contains many prescriptions for head symptoms, they are difficult to learn and apply because of the vast numbers. The aim of this study was to simplify and visualize the vast contents of Donguibogam by network analysis. Methods: 127 prescriptions for head symptoms, found in Donguibogam, were entered into a Microsoft office Excel 2013 file. This was used as a database for network analysis using the NetMiner 4 program. Results: Through network analysis, six networks for prescriptions for head symptoms in Donguibogam were established. The first network is similar to the herb composition of Cheongsangsahwa-tang (prescriptions for hwa-yeol syndrome). The second network is similar to the herb composition of Yanghyulgupung-tang (prescriptions for hyul-heo syndrome). The third network is similar to the herb composition of Sangcheongbaekbuja-hwan (prescriptions for dam-eum syndrome). The fourth network is similar to the herb composition of Heukseok-dan (prescriptions for yang-heo syndrome). The fifth network is similar to the herb composition of Boheo-eum (prescriptions for chil-jeong syndrome). The sixth network is similar to the herb composition of Bangpungtongseong-san (prescriptions for hwa-yeol syndrome). Conclusions: The results of the network analysis of 127 prescriptions for head symptoms in Donguibogam suggest that there are five major causes of head symptoms (hwa-yeol, hyul-heo, dam-eum, yang-heo, and chil-jeong), and that it is possible to prescribe Cheongsangsahwa-tang, Bangpungtongseong-san, Yanghyulgupung-tang, Sangcheongbaekbuja-hwan, Heukseok-dan, or Boheo-eum depending on the major causes.

의미 네트워크 분석법을 활용한 초등 예비교사들이 생각하는 과학에 대한 의미 분석 (An Analysis of Scientific Concepts Pre-service Elementary School Teachers Have through Semantic Network Analysis)

  • 김동렬
    • 한국초등과학교육학회지:초등과학교육
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    • 제32권3호
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    • pp.327-345
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    • 2013
  • This study aims to investigate how pre-service elementary school teachers understand 'something scientific', 'being scientific', 'scientific events' and 'scientific questions' through semantic network analysis. To achieve this purpose, this study carried out a central analysis of the frequency and density of words and the degree of connection between key words, a concentric analysis, a click analysis and a common network analysis through text semantic network analysis by using NetMiner 4.0 Program. Based on the results of these analyses, this study came to the following conclusions. Firstly, in perceiving 'something scientific', pre-service elementary school teachers recognized 'verification', 'objective' and 'experiment' as most important words. In other words, they perceived that main grounds for something scientific should be provided through clear facts, possible to be verified and accompanied by an exact and logical theoretical system. In regard to 'being scientific', they perceived 'explanation', 'objective' and 'verification' as most important words, while having a traditional point of view that science is a set that can be explained objectively. Secondly, in regard that the term, 'observation', is contained in 'scientific events', they showed a high rate of understanding it as a scientific event. In regard to scientifical reasons, they showed the highest frequency of 'observation', and for unscientific reasons, they showed the highest frequency of 'behavior'. In perceiving 'scientific questions', they showed the highest frequency of determining bacteria-related questions as scientific. As a reason why they thought as scientific, they mentioned 'observation' most frequently like 'scientific events', while mentioning 'value judgement' as a reason why they thought as unscientific most frequently. From the results of integrated network analysis, this study found out that words pre-service teachers commonly used in stating scientific events or scientific questions were overlapped with words they mentioned for scientific events or scientific questions. As a result, it was found there were many pre-service teachers having interpreted scientific words without clearly distinguishing scientific events or scientific questions.

텍스트네트워크분석을 활용한 국내·외 호스피스 간호 연구 주제의 비교 분석 (A Comparison of Hospice Care Research Topics between Korea and Other Countries Using Text Network Analysis)

  • 박은준;김영지;박찬숙
    • 대한간호학회지
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    • 제47권5호
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    • pp.600-612
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    • 2017
  • Purpose: This study aimed to identify and compare hospice care research topics between Korean and international nursing studies using text network analysis. Methods: The study was conducted in four steps: 1) collecting abstracts of relevant journal articles, 2) extracting and cleaning keywords (semantic morphemes) from the abstracts, 3) developing co-occurrence matrices and text-networks of keywords, and 4) analyzing network-related measures including degree centrality, closeness centrality, betweenness centrality, and clustering using the NetMiner program. Abstracts from 347 Korean and 1,926 international studies for the period of 1998-2016 were analyzed. Results: Between Korean and international studies, six of the most important core keywords-"hospice," "patient," "death," "RNs," "care," and "family"-were common, whereas "cancer" from Korean studies and "palliative care" from international studies ranked more highly. Keywords such as "attitude," "spirituality," "life," "effect," and "meaning" for Korean studies and "communication," "treatment," "USA," and "doctor" for international studies uniquely emerged as core keywords in recent studies (2011~2016). Five subtopic groups each were identified from Korean and international studies. Two common subtopics were "hospice palliative care and volunteers" and "cancer patients." Conclusion: For a better quality of hospice care in Korea, it is recommended that nursing researchers focus on study topics of patients with non-cancer disease, children and family, communication, and pain and symptom management.

텍스트네트워크분석을 적용한 통증관리 간호연구의 지식구조 (Identification of Knowledge Structure of Pain Management Nursing Research Applying Text Network Analysis)

  • 박찬숙;박은준
    • 대한간호학회지
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    • 제49권5호
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    • pp.538-549
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    • 2019
  • Purpose: This study aimed to explore and compare the knowledge structure of pain management nursing research, between Korea and other countries, applying a text network analysis. Methods: 321 Korean and 6,685 international study abstracts of pain management, published from 2004 to 2017, were collected. Keywords and meaningful morphemes from the abstracts were analyzed and refined, and their co-occurrence matrix was generated. Two networks of 140 and 424 keywords, respectively, of domestic and international studies were analyzed using NetMiner 4.3 software for degree centrality, closeness centrality, betweenness centrality, and eigenvector community analysis. Results: In both Korean and international studies, the most important, core-keywords were "pain," "patient," "pain management," "registered nurses," "care," "cancer," "need," "analgesia," "assessment," and "surgery." While some keywords like "education," "knowledge," and "patient-controlled analgesia" found to be important in Korean studies; "treatment," "hospice palliative care," and "children" were critical keywords in international studies. Three common sub-topic groups found in Korean and international studies were "pain and accompanying symptoms," "target groups of pain management," and "RNs' performance of pain management." It is only in recent years (2016~17), that keywords such as "performance," "attitude," "depression," and "sleep" have become more important in Korean studies than, while keywords such as "assessment," "intervention," "analgesia," and "chronic pain" have become important in international studies. Conclusion: It is suggested that Korean pain-management researchers should expand their concerns to children and adolescents, the elderly, patients with chronic pain, patients in diverse healthcare settings, and patients' use of opioid analgesia. Moreover, researchers need to approach pain-management with a quality of life perspective rather than a mere focus on individual symptoms.

SNA(Social Network Analysis)를 활용한 코로나19 전후의 가정과교육 유튜브 콘텐츠 변화 분석 (Social Network Analysis of Changes in YouTube Home Economics Education Content Before and After COVID-19)

  • 심재영;김은경;고은미;김형선;박미정
    • Human Ecology Research
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    • 제60권1호
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    • pp.1-20
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    • 2022
  • This paper presents a social network analysis of changes in Home Economics education content loaded on YouTube before and after the outbreak of COVID-19. From January 1, 2008 to June 30, 2021, a basic analysis was conducted of 761 Home Economics education videos loaded on YouTube, using NetMiner 4.3 to analyze important keywords and the centrality of video titles and full texts. Before COVID-19, there were 164 Home Economics education videos posted on YouTube, increasing significantly to 597 following the emergence of the pandemic. In both periods, there was more middle school content than high school content. The content in the child-family field was the most, and the main keywords were youth and family. Before COVID-19, a performance evaluation indicated that the proportion of student content was high, whereas after the outbreak of the disease, teacher content increased significantly due to the effect of distance learning. However, compared with video use, the self-expression and participation of users were lower in both periods. The centrality analysis indicated that in the title, 'family' exhibited a high degree of both centrality and eigenvector centrality over the entire period. Degree centrality of the video title was found to be high in the order of class, online, family, management, etc. after the outbreak of COVID-19, and the connection of keywords was strong overall. Eigenvector centrality indicated that career, search, life, and design were influential keywords before COVID-19, while class, youth, online, and development were influential keywords after COVID-19.

청소년 임신에 대한 연구 동향 분석: 텍스트 네트워크 분석과 토픽 모델링 (A study on research trends for pregnancy in adolescence: Focusing on text network analysis and topic modeling)

  • 박승미;곽은주;박혜옥;홍정은
    • 한국간호교육학회지
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    • 제30권2호
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    • pp.149-159
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    • 2024
  • Purpose: The aim of this study was to identify core keywords and topic groups in the "adolescent pregnancy" field of research for a better understanding of research trends in the past 10 years. Methods: Topics related to adolescent pregnancy were extracted from 3,819 articles that were published in journals between January 2013 and July 2023. Abstracts were retrieved from five databases (MEDLINE, CINAHL, Embase, RISS, and KISS). Keywords were extracted from the abstracts and cleaned using semantic morphemes. Text network analysis and topic modeling were performed using NetMiner 4.3.3. Results: The most important keywords were "health," "woman," "risk," "group," "girl," "school," "service," "family," "program," and "contraception." Five topic groups were identified through topic modeling. Through the topic modeling analysis, five themes were derived: "health service," "community program for school girls," "risks for adult women," "relationship risks," and "sexual contraceptive knowledge." Conclusion: This study utilized text network analysis and topic modeling to analyze keywords from abstracts of research conducted over the past decade on adolescent pregnancy. Given that adolescent pregnancy leads to physical, mental, social, and economic issues, it is imperative to provide integrated intervention programs, including prenatal/postnatal care, psychological services, proper contraception methods, and sex education, through school and community partnerships, as well as related research studies. Nurses can play a vital role by actively engaging in prevention efforts and directly supporting and educating socially disadvantaged adolescent mothers, which could significantly contribute to improving their quality of life.

다계층 이원 네트워크를 활용한 사용자 관점의 이슈 클러스터링 (User-Perspective Issue Clustering Using Multi-Layered Two-Mode Network Analysis)

  • 김지은;김남규;조윤호
    • 지능정보연구
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    • 제20권2호
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    • pp.93-107
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    • 2014
  • 대부분의 인터넷 쇼핑몰은 자사 고객의 관심 분야를 파악하고 이를 상품 추천에 효과적으로 활용하기 위해 많은 노력을 기울이고 있다. 하지만 고객이 회원 가입 시 직접 입력한 개인 정보는 신뢰하기가 어렵고, 고객의 구매 패턴을 통해 파악한 관심 분야 정보는 자사 사이트 내에 진입한 이후에만 보인 한정된 패턴이라는 측면에서 해당 고객의 다양한 관심분야를 제대로 나타낸다고 보기 어렵다. 이러한 한계를 극복하기 위해 본 연구에서는 고객의 평소 인터넷 사용 기록을 통해 최근 방문 사이트들의 주제를 분석함으로써, 고객의 실제 관심 분야를 파악할 수 있는 방안을 제시하였다. 또한 토픽 분석을 통해 각 사이트의 주제를 도출하고 도출된 주제를 다시 동시 방문자 관점에서 군집화 함으로써, 고객 관점에서 의미가 있는 상위 수준의 새로운 테마를 발굴하기 위한 방법론을 제안하였다. 연구의 특징은 유사주제 중심의 군집화라는 기존 연구와는 달리 사용자 관점의 관심주제 중심 군집화라 할 수 있다. 향후 사용자 중심의 카테고리 설계를 비롯한 새로운 관점의 고객군 정의 등 보다 높은 차원의 마케팅 전략 수립에 활용이 가능할 것으로 기대된다. 사용자 관점의 이슈 군집화 과정은 크롤링, 토픽 분석, 액세스 패턴 분석, 네트워크 병합, 네트워크 변환 및 군집화와 같은 여섯 가지 주요단계로 구성되어있다. 이를 위해 텍스트 마이닝과 소셜 네트워크 분석 기법을 활용한 비정형 텍스트를 기반으로한 빅데이터의 활용 방법을 모색하였다. 제안 방법론의 실무 적용 가능성을 평가하기 위해, 국내 최대 포털 뉴스 사이트의 방문자 2,177명의 1년간 방문 기록과 뉴스기사 대한 분석을 수행하고 그 결과를 요약하여 제시하였다.