• Child Health Nursing Research
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• v.29 no.3
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• pp.182-194
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• 2023

Purpose: This study analyzed research trends in infant and toddler rearing behavior among family caregivers over a 10-year period (2010-2021). Methods: Text network analysis and topic modeling were employed on data collected from relevant papers, following the extraction and refinement of semantic morphemes. A semantic-centered network was constructed by extracting words from 2,613 English-language abstracts. Data analysis was performed using NetMiner 4.5.0. Results: Frequency analysis, degree centrality, and eigenvector centrality all revealed the terms ''scale," ''program," and ''education" among the top 10 keywords associated with infant and toddler rearing behaviors among family caregivers. The keywords extracted from the analysis were divided into two clusters through cohesion analysis. Additionally, they were classified into two topic groups using topic modeling: "program and evaluation" (64.37%) and "caregivers' role and competency in child development" (35.63%). Conclusion: The roles and competencies of family caregivers are essential for the development of infants and toddlers. Intervention programs and evaluations are necessary to improve rearing behaviors. Future research should determine the role of nurses in supporting family caregivers. Additionally, it should facilitate the development of nursing strategies and intervention programs to promote positive rearing practices.

• Journal of Korean Academy of Nursing
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• v.52 no.3
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• pp.291-307
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• 2022

Purpose: The aims of study were to identify the main keywords, the network structure, and the main topics of press articles related to nurses that have appeared in media reports. Methods: Data were media articles related to the topic "nurse" reported in 16 central media within a one-year period spanning July 1, 2019 to June 30, 2020. Data were collected from the Big Kinds database. A total of 7,800 articles were searched, and 1,038 were used for the final analysis. Text network analysis and topic modeling were performed using NetMiner 4.4. Results: The number of media reports related to nurses increased by 3.86 times after the novel coronavirus (COVID-19) outbreak compared to prior. Pre- and post-COVID-19 network characteristics were density 0.002, 0.001; average degree 4.63, 4.92; and average distance 4.25, 4.01, respectively. Four topics were derived before and after the COVID-19 outbreak, respectively. Pre-COVID-19 example topics are "a nurse who committed suicide because she could not withstand the Taewoom at work" and "a nurse as a perpetrator of a newborn abuse case," while post-COVID-19 examples are "a nurse as a victim of COVID-19," "a nurse working with the support of the people," and "a nurse as a top contributor and a warrior to protect from COVID-19." Conclusion: Topic modeling shows that topics become more positive after the COVID-19 outbreak. Individual nurses and nursing organizations should continuously monitor and conduct further research on nurses' image.

• Journal of dental hygiene science
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• v.23 no.4
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• pp.302-311
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• 2023

Background: Oral health is an important element of well aging. And oral health also affects overall health, mental health, and quality of life. In this study, we sought to identify oral health influencing factors and research trends for well-aging through text analysis of research on well-aging and oral health over the past 12 years. Methods: The research data was analyzed based on English literature published in PubMed from 2012 to 2023. Aging well and oral health were used as search terms, and 115 final papers were selected. Network text analysis included keyword frequency analysis, centrality analysis, and cohesion structure analysis using the Net-Miner 4.0 program. Results: Excluding general characteristics, the most frequent keywords in 115 articles, 520 keywords (Mesh terms) were psychology, dental prosthesis and Alzheimer's disease, Dental caries, cognition, cognitive dysfunction, and bacteria. Research keywords with high degree centrality were Dental caries (0.864), Quality of life (0.833), Tooth loss (0.818), Health status (0.727), and Life expectancy (0.712). As a result of community analysis, it consisted of 4 groups. Group 1 consisted of chewing and nutrition, Group 2 consisted oral diseases, systemic diseases and management, Group 3 consisted oral health and mental health, Group 4 consisted oral frailty symptoms and quality of life. Conclusion: In an aging society, oral dysfunction affects mental health and quality of life. Preventing oral diseases for well-aging can have a positive impact on mental health and quality of life. Therefore, efforts are needed to prevent oral frailty in a super-aging society by developing and educating systematic oral care programs for each life cycle.

• Journal of Internet of Things and Convergence
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• v.4 no.1
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• pp.23-29
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• 2018

The purpose of study was to analyze the trends of 2005 to 2018 revised 'convergence technology research' through text network analysis using NetMiner4.0 program. Data analysis was conducted by using keyword analysis, centrality analysis of 653 authors' keyword from 177 journals. The results of the study are as follows. First, Research on Converging Technology has been studied steadily over the past 13 years in Department of Industry Convergence. Second, the results of the search term frequency analysis show that the 'convergence technology', 'technology convergence', 'convergence', 'design', 'convergence education', 'STEAM', 'convergence research' were used as the main keywords of convergence technology research. Third, Community analysis results show that five communities have been classified five categories according to the characteristics of the search terms 'only IT', 'Cultural industry utilizing Convergence contents', 'Technology innovation and research analysis' And patent development'. Based on these results, we proposed the future directions of convergence technology research.

• Journal of East-West Nursing Research
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• v.26 no.2
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• pp.118-129
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• 2020

Purpose: The purpose of this study was to analyze the topic trend of domestic simulation nursing education research using text network analysis(TNA). Methods: This study was conducted in four steps. TNA was performed using the NetMiner (version 4.4.1) program. Firstly, 245 articles from 4 databases (RISS, KCI, KISS, DBpia) published from 2008 to 2018, were collected. Secondly, keyword-forms were unified and representative words were selected. Thirdly, co-occurrence matrices of keywords with a frequency of 2 or higher were generated. Finally, social network-related measures-indices of degree centrality and betweenness centrality-were obtained. The topic trend over time was visualized as a sociogram and presented. Results: 178 author keywords were extracted. Keywords with high degree centrality were "Nursing student", "Clinical competency", "Knowledge", "Critical thinking", "Communication", and "Problem-solving ability." Keywords with high betweenness centrality were "CPR", "Knowledge", "Attitude", "Self-efficacy", "Performance ability", and "Nurse." Over time, the topic trends on simulation nursing education have diversified. For example, topics such as "Neonatal nursing", "Obstetric nursing", "Pediatric nursing", "Blood transfusion", "Community visit nursing", and "Core basic nursing skill" appeared. The core-topics that emerged only recently (2017-2018) were "High-fidelity", "Heart arrest", "Clinical judgment", "Reflection", "Core basic nursing skill." Conclusion: Although simulation nursing education research has been increasing, it is necessary to continue studies on integrated simulation learning designs based on various nursing settings. Additionally, in simulation nursing education, research is required not only on learner-centered educational outcomes, but also factors that influence educational outcomes from the perspective of the instructors.

• Human Ecology Research
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• v.60 no.4
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• pp.625-643
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• 2022

The purpose of this study was to explore the trends and core keywords of the secondary school home economics teacher selection test using content analysis and text network analysis. The sample comprised texts of the secondary school home economics teacher 1st selection test for the 2017-2022 school years. Determination of frequency of occurrence, generation of word clouds, centrality analysis, and topic modeling were performed using NetMiner 4.4. The key results were as follows. First, content analysis revealed that the number of questions and scores for each subject (field) has remained constant since 2020, unlike before 2020. In terms of subjects, most questions focused on 'theory of home economics education', and among the evaluation content elements, the highest percentage of questions asked was for 'home economics teaching·learning methods and practice'. Second, the network of the secondary school home economics teacher selection test covering the 2017-2022 school years has an extremely weak density. For the 2017-2019 school years, 'learning', 'evaluation', 'instruction', and 'method' appeared as important keywords, and 7 topics were extracted. For the 2020-2022 school years, 'evaluation', 'class', 'learning', 'cycle', and 'model' were influential keywords, and five topics were extracted. This study is meaningful in that it attempted a new research method combining content analysis and text network analysis and prepared basic data for the revision of the evaluation area and evaluation content elements of the secondary school home economics teacher selection test.

• Korean Journal of Health Education and Promotion
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• v.22 no.2
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• pp.173-193
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• 2005

Objectives: The purpose of this study is to analyze the peer group factor related to adolescent smoking in the social structure(network) of adolescent groups, by applying the theory of social network. Methods: The data was collected from boy students of one high school located in Gun-Po city of Kyonggi Province. The total number of the sample was 605(223 first grade, 198 second grade, 184 third grade). The survey using the questionnaire was carried out in April 2005. Social position is finally classified as clique member, liaison, isolate group by using the NetMiner II 2.5 version. Results: The current smoking rate was 15.0%, and the life-time smoking rate was 34.9%. The smoking rate increased significantly, as the grade went up. And it was significantly high among the group having smoking friends. The logistic regression analysis showed that the odds ratio of the smoking friends group was about 4 times higher than the no smoking friends group in experience of smoking. But the smoking rate was higher significantly in the isolate group within the network composed of 2. person's social-link. The odds ratio of the isolate group was about 4.5 times higher than the clique member. However, this pattern was not found in the network composed of 3 person's social-link. Therefore, the hypothesis that clique member would have a correlation with smoking was rejected. In reality, the isolate group had a tendency of smoking more frequently. Conclusions: The result of this study suggests that the role of the peer group in smoking is to be considered in the prevention program. More attentions should be paid for the isolate group.

• Journal of Korean Elementary Science Education
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• v.33 no.4
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• pp.674-682
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• 2014

This study aims to analyze STEAM-related articles and to look into the trend of research to present implications for research directions in the future. To achieve the research purpose, the researcher searched by key words, 'STEAM' and 'Convergence Education' through the RISS. Subjects of analysis were titles of 181 articles in journal articles and conference papers published from 2011 through 2013. Through an analysis of the frequency of the texts that appeared in the titles of the papers, key words were selected, the co-occurrence matrix of the key words was established, and using network maps, degree centrality and betweenness centrality, and structural equivalence, a network text analysis was carried out. For the analysis, KrKwic, KrTitle, UCINET and NetMiner Program were used, and the results were as follows: in the result of the text frequency analysis, the key words appeared in order of 'program', 'development', 'base' and 'application'. Through the network among the texts, a network built up with core hubs such as 'program', 'development', 'elementary' and 'application' was found, and in the degree centrality analysis, 'program', 'elementary', 'development' and 'science' comprised key issues at a relatively high value, which constituted the pivot of the network. As a result of the structural equivalence analysis, regarding the types of their respective relations, it was analyzed that there was a similarity in four clusters such as the development of a program (1), analysis of effects (2) and the establishment of a theoretical base (1).

• Journal of health informatics and statistics
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• v.43 no.4
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• pp.274-281
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• 2018

Objectives: The purpose of this study is to comprehensively compare the trends of health administration and health policy in the field of health care using the semantic network analysis in the inaugural address of the Ministry of Health and Welfare of each regime in Korea. Methods: This study used a language network analysis method that uses Korean Key Words In Context (KrKwic) program and NetMiner program in sequence. The analysis was conducted by Minister Hwa-joong Kim during the Moo-hyun Roh government, Minister Jae-hee Jeon during the Myung-bak Lee government, Minister Young Jin of Geun-hye Park government and Government Jae-in Moon's inaugural address of Neung-Hoo Park Minister, respectively. Results: The key words differentiated by each regime are that the Moo-hyun Roh Government's Minister Hwa-joong Kim had high connection centrality values in the words 'balanced development', 'comprehensive' and 'reform'. Minister Jae-Hee Jeon of Myung-bak Lee Government had high connection centrality values in the words 'poverty' and 'return'. In the case of Minister Young Jin of Geun-hye Park Government had high connection centrality values in the words 'demand', 'Customized' and 'Life cycle'. In the case of Minister Neung-Hoo Park of Jae In Moon Government had high connection centrality values in the words 'Welfare state', 'Embracing' and 'Soundness'. Conclusions: If the role of health administration in the health care field and the health care policies are constantly changed according to the policies of each regime, it is inconsistent and it is difficult to approach from the long term perspective for public health promotion. In the future, health policy should be developed and implemented with a long-term perspective and consistency based on the consensus and participation of the people with less influence on the change and direction of each government's policies.

• Journal of the Korea Convergence Society
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• v.10 no.4
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• pp.229-236
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• 2019

The purpose of this paper is to analyze social phenomena and perceptions by collecting and analyzing data on public opinion, views and trends related to special case of military service in the sports community through Big KINDS operated by the Korea Press Promotion Foundation. To this end, the related keywords were derived and visualized by implementing a LDA(latent dirichlet allocation) technique to derive problems found in social phenomena based on big data analysis. The topics derived include "re-lighting special case on military service," " military service corruption controversy," "special case of military service for athletes," "alternative military service system for artists " and "parliamentary inspection of the administration" This could be used as a basic data for identifying accurate information on social controversies related to special case of military service in the sports community and drawing up practical measures that are considered in line with the principle of just and equal burden.