• Journal of the Korea Convergence Society
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• v.13 no.2
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• pp.1-12
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• 2022

The purpose of this study is to identify the social perception characteristics of young children with disabilities over the past decade. For this purpose, Textom, an Internet-based big data analysis system was used to collect data related to young children with disabilities posted on social media. 50 keywords were selected in the order of high frequency through the data cleaning process. For semantic network analysis, centrality analysis and CONCOR analysis were performed with UCINET6, and the analyzed data were visualized using NetDraw. As a result, the keywords such as 'education, needs, parents, and inclusion' ranked high in frequency, degree, and eigenvector centrality. In addition, the keywords of 'parent, teacher, problem, program, and counseling' ranked high in betweenness centrality. In CONCOR analysis, four clusters were formed centered on the keywords of 'disabilities, young child, diagnosis, and programs'. Based on these research results, the topics on social perception of young children with disabilities were investigated, and implications for each topic were discussed.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.2
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• pp.97-122
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• 2023

Metaliteracy is a new framework that reframes information literacy. Metaliteracy is distinguished from information literacy through the intruduction of postmodernism, social constructivism and metacognition. However it has been not examined whether metaliteracy studies reflect the conceptual differences. Therefore, The purpose of the study is to observe research trends of metaliteracy on the difference from information literacy. In the study, literature reviews were conducted, and frequency analysis and knowledge network analysis(co-occurrence and bibliographic coupling) were conducted for 80 metaliteracy studies. The results of the study are as follows. As a result of co-occurrence analysis, metacognition(frequency 1st) and skills(degree centrality 1st, closeness centrality 1st, betweenness centrality 1st) appeared. Since metaliteracy criticizes skill-based information literacy, the result suggests that the concepts of information literacy and metaliteracy are mixed. On the other hand, as a result of bibliographic coupling analysis, studies with high bibliographic coupling explain the difference between information literacy and metaliteracy through metacognition.

• Korean Journal of Acupuncture
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• v.40 no.4
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• pp.177-183
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• 2023

Objectives : One of the crucial combinations of acupoints for treating various disorders involves the Eight Confluent acupoints. The present study aims to investigate the selection patterns of the Eight Confluent acupoints in clinical trials and determine the most frequent pairings through network analysis. Methods : The frequencies of the Eight Confluent acupoints were extracted from the Acusynth database, which includes data from 421 clinical investigations. We examined the degree distribution, eigenvector centrality, proximity centrality, and betweenness centrality of these acupoint combinations using network analysis. Results : Data mining revealed that among the Eight Confluent acupoints, PC6 and TE5 were the most commonly applied in the treatment of 30 disorders. Additionally, we identified the most frequently co-occurring pairs of Eight Confluent acupoints by network analysis which included PC6-GV20, SP4-GV4, LU7-LI4, TE5-PC7, GB41-SP6, KI6-BL62, and SI3-BL62. Conclusions : Through the application of data mining and network analysis, we have elucidated the selection patterns and combinations of the Eight Confluent acupoints. These findings provide valuable insights that can enhance doctors' understanding of clinical database-driven Eight Confluent acupoint selection patterns.

• Asian Journal of Innovation and Policy
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• v.6 no.1
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• pp.85-93
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• 2017

This paper focuses on the relationship between the characteristics of network and the productivity of scientists, which is rarely examined in previous studies. Utilizing a unique dataset from the Korean Citation Index (KCI), we examine the overall characteristics of the research network (e.g. distribution of nodes, density and mean distance), and analyze whether the network centrality is related to the scientific productivity. According to the results, firstly we have found that the collaborative research network of the Korean academics in the field of statistics and computer science is a scale-free network. Secondly, these research networks show a disciplinary difference. The network of statisticians is denser than that of computer scientists. In addition, computer scientists are located in a fragmented network compared to statisticians. Thirdly, with regard to the relationship between the researchers' network position and scientific productivity, a significant relation and their disciplinary difference have been observed. In particular, the degree centrality is the strongest predictor for the scientists' productivity. Based on these findings, some policy implications are put forward.

• Knowledge Management Research
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• v.19 no.3
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• pp.189-223
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• 2018

This paper examined the effect of innovation networks comprising research and development (R&D) collaboration on innovation performance of Korean pharmaceutical firms. As co-assigned patents and co-affiliated publications are common technical outcomes of successful R&D collaboration in the pharmaceutical industry, social network analysis technique was applied for analyzing innovation networks through patent and publication data. Results of Social network analysis indicated that a small set of highly innovative firms in the Korean pharmaceutical industry were actively involved in patenting and publishing. And the analysis of structural equation model found the followings: (1) R&D intensity significantly affected patenting, publication and new drug development, (2) the activity of patenting and publishing was positively related with the innovation performance measured by new drug development, and (3) R&D collaboration in terms of degree centrality of co-patent network played significant moderating roles on the relationships among R&D intensity, patenting, and new drug development. These findings are expected to be helpful to researchers as well as policy-makers to devise innovation-promoting policies in the Korean pharmaceutical industry. Discussions and limitations of the study are provided in the last part.

• Journal of Korean Elementary Science Education
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• v.39 no.2
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• pp.255-267
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• 2020

Students' engagement is important for meaningful learning and it has multifaceted aspects for their science learning. This study investigated elementary students' perceptions of science learning engagement. The subjects of this study were 341 4^th to 6^th elementary students. The survey questionnaires were 5-Likert scale questions and free response questions on science learning engagement. The results showed that elementary students' perceptions of behavioral engagement were higher than emotional and cognitive engagement. Keyword network analysis with NetMiner program showed that the frequent key words of science learning engagement were 'experiment', 'listening', and 'teachers' explanation', which were mostly the behavioral types of engagement. The degree centrality and eigenvector centrality of these key words appeared high. 'Interest', which is emotional engagement, were also one of the frequent key words, but the centralities of this word were relatively low. The Frequent key words of science learning disengagement were mostly related with off-tasks, not doing expected behaviors and negative emotions about science and science learning. Educational implications on science learning engagement were discussed.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.21 no.3
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• pp.67-81
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• 2018

We tried to analyze qualitatively a total of 110 the research papers which were related domestic ecological restoration technologies about 15 years through semantic network analysis in social network analysis. In order to understand the research trends of ecological restoration technologies, we analyzed the degree centrality and betweenness centrality of the Stream/Wetland, Slope, Soil/Others fields selected as Word Cloud. As a result, ecological restoration technologies have been changed. They were focused on the restoration of species or their habitats in the past. However, they have been evolved into the detailed systems to respond in unpredictable natural disasters and climate change, high-resolution image implementation technology to accurately grasp the practical environment and methods related to environmental restoration for human in urban ecosystem. In the future, investment and technology for the ecosystem restoration field will be continuously demanded for the symbiosis of human beings and species in the damaged ecosystem. Therefore, the research trend of ecological restoration technologies should be provided as reliable guidelines when decision makers establish the policy direction or when researchers select their subjects.

• Culinary science and hospitality research
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• v.23 no.4
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• pp.22-32
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• 2017

The purpose of this study was to explore awareness of food tourism using big data analysis. For this, this study collected data containing 'food tourism' keywords from google web search, google news, and google scholar during one year from January 1 to December 31, 2016. Data were collected by using SCTM (Smart Crawling & Text Mining), a data collecting and processing program. From those data, degree centrality and eigenvector centrality were analyzed by utilizing packaged NetDraw along with UCINET 6. The result showed that the web visibility of 'core service' and 'social marketing' was high. In addition, the web visibility was also high for destination, such as rural, place, ireland and heritage; 'socioeconomic circumstance' related words, such as economy, region, public, policy, and industry. Convergence of iterated correlations showed 4 clustered named 'core service', 'social marketing', 'destinations' and 'social environment'. It is expected that this diagnosis on food tourism according to changes in international business environment by using these web information will be a foundation of baseline data useful for establishing food tourism marketing strategies.

• Journal of the Korea Convergence Society
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• v.9 no.2
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• pp.251-257
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• 2018

As the use of big data is necessary for increasing business value, the size of the big data market is getting bigger. Accordingly, it is important to apply competitive patents in order to gain the big data market. In this study, we conducted the patent analysis based keyword network to analyze the trend of big data patents. The analysis procedure consists of big data collection and preprocessing, network construction, and network analysis. The results of the study are as follows. Most of big data patents are related to data processing and analysis, and the keywords with high degree centrality and between centrality are "analysis", "process", "information", "data", "prediction", "server", "service", and "construction". we expect that the results of this study will offer useful information in applying big data patent.

• Child Health Nursing Research
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• v.27 no.3
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• pp.201-210
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• 2021

Purpose: This study analyzed research trends related to childhood and adolescent cancer survivors (CACS) using word co-occurrence network analysis on studies registered in the Korean Citation Index (KCI). Methods: This word co-occurrence network analysis study explored major research trends by constructing a network based on relationships between keywords (semantic morphemes) in the abstracts of published articles. Research articles published in the KCI over the past 10 years were collected using the Biblio Data Collector tool included in the NetMiner Program (version 4), using "cancer survivors", "adolescent", and "child" as the main search terms. After pre-processing, analyses were conducted on centrality (degree and eigenvector), cohesion (community), and topic modeling. Results: For centrality, the top 10 keywords included "treatment", "factor", "intervention", "group", "radiotherapy", "health", "risk", "measurement", "outcome", and "quality of life". In terms of cohesion and topic analysis, three categories were identified as the major research trends: "treatment and complications", "adaptation and support needs", and "management and quality of life". Conclusion: The keywords from the three main categories reflected interdisciplinary identification. Many studies on adaptation and support needs were identified in our analysis of nursing literature. Further research on managing and evaluating the quality of life among CACS must also be conducted.