• Human Ecology Research
• /
• v.60 no.1
• /
• pp.1-20
• /
• 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.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.3
• /
• pp.81-94
• /
• 2023

The study aims to compare and analyze the social network structures of Qatar Airways,s Singapore Airlines, Emirates Airlines, and ANA Airlines, recording the top 1 to 4, and Korean Air in ninth by Skytrax's airline evaluations in 2022. This study uses NodeXL, a social network analysis program, to analyze the social networks of 5 airlines, Vertex, Unique Edges, Single-Vertex Connected Components, Maximum Geodesic Distance, Average Geodesic Distance, Average Degree Centrality, Average Closeness Centrality, and Average Betweenness Centrality as indicators to compare the differences in these social networks of the airlines. As a result, Singapore's social network has a better network structure than the other airlines' social networks in terms of sharing information and transmitting resources. In addition, Qatar Airways and Singapore Airlines are superior to the other airlines in playing roles and powers of influencers who affect the flow of information and resources and the interaction within the airline's social network. The study suggests some implications to enhance the usefulness of social networks for marketing.

• Korea Trade Review
• /
• v.47 no.2
• /
• pp.121-132
• /
• 2022

This study aims to find out the ESG management keywords in the logistics industry through social network analysis using news article and sustainable management reports. In recent years, global climate change and Covid-19 have spurred companies to step up their new management system called ESG management. ESG is a combination of Environment, Social, and Governance. In the past, companies' financial performance was the most important, but in the current investment market, the movement to reflect ESG management factors in investment decisions is strengthening. This study aims to find out degree centrality, betweenness centrality, and closeness centrality through social network analysis after collecting related keywords to derive ESG management issues of logistics companies. This study collected 2,359 news articles searched under the keywords "ESG", "Logistics". In addition, data on ESG activities were also used for analysis by referring to the sustainable management reports of logistics companies. As a result of the analysis of degree centrality, it was found that ESG management of logistics companies is in progress, focusing on small enterprises and eco-friendly keywords, and is concentrated on social responsibility and eco-friendly activities. In the betweenness centrality analysis, logistics companies such as HMM and CJ Logistics were derived in a high ranking. In the closeness centrality analysis, eco-friendly keywords topped the list, while the number of keywords related to governance was relatively small, suggesting that logistics companies need to improve their governance structure.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.46 no.6
• /
• pp.1058-1073
• /
• 2022

Big data analytics and social media have shifted the way fashion trends are dictated. Fashion as a medium for expressing gender has created new concepts of masculinity in popular culture, where men are increasingly depicted in a softer style. In this study, we analyzed 2,879 menswear collections over a 10-year period from Vogue US to uncover key menswear trends. Using Semantic Network Analysis (SNA) on Orange3, we were able to quantitatively analyze how contemporary menswear designers interpreted diversified trends of masculinity on the runway. Frequency and degree centrality were measured to weigh the significance of trend keywords. "Jacket (f = 3056; DC = 0.80), shirt (f = 1912; DC = 0.60) and pant (f = 1618; DC = 0.53)" were among the most prominent keywords. Our results showed that soft masculine keywords, e.g., "lace, floral, and pink" also appeared, but with the majority scoring DC = < 0.10. The findings provide an insight into key menswear trends through frequency, degree centrality measurements, time-series analysis, egocentric, and visual semantic networks. This also demonstrates the feasibility of using text analytics to visualize design trends, concepts, and patterns for application as an ideation tool for academic researchers, designers, and fashion retailers.

• Journal of Korean Society of Transportation
• /
• v.28 no.3
• /
• pp.85-98
• /
• 2010

As transit networks are becoming more multimodal, the concept of connectivity of transit networks becomes important. This study aims to develop a quantitative model for measuring the connectivity of multimodal transit networks. To that end, we select, as evaluation measures of a transit line, its length, capacity, and speed. We then define the connecting power of a transit line as the product of those measures. The degree centrality of a node, which is a widely used centrality measure in social network analysis, is employed with appropriate modifications suited for transit networks. Using the degree centrality of a transit stop and the connecting powers of transit lines serving the transit stop, we develop an index quantifying the level of connectivity of the transit stop. From the connectivity indexes of transit stops, we derive the connectivity index of a transit line as well as an area of a multimodal transit network. In addition, we present a method to evaluate the connectivity of a transfer center using the connectivity indexes of transit stops and passenger acceptance rate functions. A case study shows that the connectivity evaluation model developed in this study takes well into consideration characteristics of multimodal transit networks, adequately measures the connectivity of transit stops, lines, and areas, and furthermore can be used in determining the level of service of transfer centers.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.6
• /
• pp.137-146
• /
• 2018

The purpose of this study was to derive and analyze the hub facilities that occupy major positions in the vehicle movement networks of livestock facilities. For this purpose, this study used the KAHIS data provided by Animal and Plant Quarantine Agency. The hub facilities were derived from the degree centrality & betweenness centrality. The analysis results are summarized as follows. First, in a livestock facility's vehicle movement network, there are a small number of hub facilities with very high centrality indicator values compared to other facilities. Second, the hub facilities based on the degree centrality are the feed factory, the milk collecting center, slaughterhouse, slaughterhouse for chicken, and livestock markets. Third, the hub facilities based on the betweenness centrality are the livestock markets, the feed factory, and slaughterhouse. Fourth, hub facilities based on the degree centrality are concentrated in a particular area, but the hub facilities based on betweenness centrality are distributed relatively evenly.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.14 no.2
• /
• pp.447-452
• /
• 2019

The elder problem is very serious stage in the age of present. This paper carries out scientometric analysis based on keyword that effort of global researcher for this research field as viewpoint of ICT and healthcare in order to settle physical exercise and rehabilitation of elder. First, this paper performs analysis of linkage relation of keyword. Second this paper carries out the analysis of degree distribution and centrality analysis of network based on betweenness centrality, closeness centrality and harmony centrality. Through this process, this paper reviews research trend of present and future through core keyword in the field of ICT and healthcare.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.18 no.3
• /
• pp.9-23
• /
• 2022

This study aims to examine research trends on the Internet of Things and smart city based on papers from the United States, Japan, and Korea. We collected 7113 papers related to the Internet of Things and smart city published from 2016 to 2021 in Elsevier's Scopus. Keyword frequency and centrality analysis were performed based on the abstracts of the collected papers. We found keywords with high frequency of appearance by calculating keyword frequency and identified central research keywords through the centrality analysis by country. As a result of the analysis, research on security, machine learning, and edge computing related to the Internet of Things and smart city were the most central and highly mediating research conducted in each country. As an implication, studies related to deep learning, cybersecurity, and edge computing in Korea have lower degree centrality and betweenness centrality compared to the United States and Japan. To solve the problem it is necessary to combine these studies with various fields. The future research direction is to analyze research trends on the Internet of Things and smart city in various regions such as Europe and China.

• Korea Trade Review
• /
• v.47 no.6
• /
• pp.189-209
• /
• 2022

This study aims to analyze Latin America and the Caribbean papers published in Korea during the past 2000-2020 years. Through this study, it is possible to understand the main subject and direction of research in Korea's Latin America and the Caribbean area. As the research mythologies, this study uses the text mining and Social Network Analysis such as frequency analysis, several centrality analyses, and topic analysis. After analyzing the empirical results, there has been a tendency to change the key words and centrality coefficients between 2000-2010 and 2011-2020 years. During 2011-2020 years, the most frequent keywords were changed from Neoliberalism and culture to policy education, and economy related words. The degree and closeness centrality analyses appeared the higher frequency key words. However, the eigenvector centrality appeared very different from the order of frequency key words. The topic analysis shows that the culture, language, and Neoliberalism were the most important keywords during 2000-2010 years but economy, labor trade, industry, development became the most important keywords during 2011-2020 years in topics.

• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.37 no.4
• /
• pp.73-80
• /
• 2019

This is an empirical study to investigate the types of plants used in Gertrude Jekyll's wild gardens, identify relationships between plants, and analyze the planting patterns. Four sites were chosen for the study: the Cotswold Cottage, the Dryton Wood, the Little Aston, and the Frant Court. To find direct relationships between plants from the planting patterns shown in these gardens, the social network analysis program R was used to analyze degree centrality, which resulted in the identification of top three plants, followed by looking into their characteristics and meanings. The summary of the results is: Azaleas(Rhododendron spp.) showed the highest degree centrality, followed by wild roses (Rosa spp.). Cold-resistant crossbreed azaleas were used as underplanting connected to many different plants, creating the feeling of an atypical woodland garden. As an indigene, wild roses showed high degree centrality in terms of ecology and aesthetics, forming multiple layer planting. Also, plants with small white flowers, for example rowans(Sorbus commixta), shadbush(Amelanchier asiatica), sealwort(Polygonatum odoratum), and American columbines(Aquilegia vulgaris) were planted in these wild gardens as plant colonies to make natural connections with other plants through drifts.