• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.6
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• pp.1058-1073
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• 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 Preventive Medicine and Public Health
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• v.41 no.6
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• pp.365-372
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• 2008

Objectives : There are very few researches on North Korea's academic activities. Furthermore, it is doubtful that the available data are reliable. This study investigated research activities and knowledge structure in the field of Preventive Medicine in North Korea with a network analysis using co-authors and keywords. Methods : The data was composed of the North Korean Journal of preventive medicine ranged from Vol. 1 of 1997 to Vol. 4 of 2006. It was the matrix of 1,172 articles by 1,567 co-authors. We applied R procedure for keywords abstraction, and then sought for the outcome of network forms by spring-KK and shrinking network. Results : To comprehend the whole networks explicitly demonstrated that the academic activities in North Korea s preventive medicine were predisposed to centralization as similar as South Korea's, but on the other aspect they were prone to one-off intermittent segmentation. The principal co-author networks were formulated around some outstanding medical universities seemingly in addition to possible intervention by major researchers. The knowledge structure of network was based on experimentation judging from keywords such as drug, immunity, virus detection, infection, bacteria, anti-inflammation, etc. Conclusions : Though North Korea is a socialist regime, there were network of academic activities, which were deemed the existence of inducive mechanism affordable for free research. Article keywords has laid greater emphasis on experiment-based bacterial defection, sustainable immune system and prevention of infection. The kind of trend was a consistent characteristic in preventive medicine of North Korea haying close correlation with Koryo medical science.

• Journal of Korean Academy of Nursing
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• v.47 no.5
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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.

• Journal of Technology Innovation
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• v.24 no.4
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• pp.101-126
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• 2016

This paper identifies core research topics and their relationships by deriving the research topic networks in the technology management field using co-word analysis. Contrary to the conventional approach in which undirected networks are constructed based on normalized co-occurrence frequency, this study analyzes directed networks of keywords by employing the confidence index of association rule mining for pairs of keywords. Author keywords included in 2,456 articles published in nine international journals of technology management in 2011~2014 are extracted and categorized into three types: THEME, METHOD, and FIELD. One-mode networks for each type of keywords are constructed to identify core research keywords and their interrelationships with each type. We then derive the two-mode networks composed of different two types of keywords, THEME-METHOD and THEME-FIELD, to explore which methods or fields are frequently employed or studied for each theme. The findings of this study are expected to be fruitfully referred for researchers in the field of technology management to grasp research trends and set the future research directions.

• Journal of Korean Home Economics Education Association
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• v.35 no.1
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• pp.105-124
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• 2023

The purpose of this study was to identify the characteristics of the contents included in the curriculum and 382 syllabi of the department of home economics education of College of Education in Korea and analyze the correlation by detailed area through the keyword network method. In order to analyze the home economics education curriculum and 382 syllabuses of a total of 11 universities, the frequency of keyword occurrence was analyzed using the KrKwic program, also the degree of connection between keywords and various centrality scales were calculated and visualized. The results of this study were as follows. First, as a result of analyzing the entire syllabi, keywords representing various fields such as family, secondary school, clothing, food, consumer, and design appeared evenly, and keywords related to teaching methods such as 'method', 'practice', 'change', and 'principle' were appeared. Those keywords showed high degree of connection and centrality. Second, in the detailed sectoral analysis, core keywords for each area appeared, and each subject were found to reflect the core keywords of the academic base. This study contributes to the conversion of curriculum of the department of home economics education to future-oriented and convergent curriculum.

• The Journal of the Korea Contents Association
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• v.12 no.8
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• pp.207-214
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• 2012

The purpose of this study was to review the agreement and disagreement logics on privatization of health care to bring quality enhancement of medical service and alienated area without medical services at the same time, to identify the core keywords through language network analysis a kind of contents analysis on the editorials dealing with privatization of health care and hospitals for profit published on the major daily newspapers for the recent three years, and to find out what is the core of the controversy through the connection centrality analysis of core keywords. Conclusively, it was found from the centrality analysis that "medical service," "hospital," "privatization," "privatization of health care," "hospital for profit" and "Government" were situated in the center of the controversy. It is natural that keywords such as "medical service," "hospital," "privatization," "privatization of health care"and "hospital for profit" were located in the center because this study reviewed the editorials published on major newspapers for the recent three years regarding the privatization of health care or hospital for profit. Next important keywords (words) were "people," "health"and "health insurance." It shows that privatization of health care was not simply seen as the opening of medical service market but as an important issue related to health of people and health Insurance. Next words with high centrality were "objection" and "allowance." Through the contents analysis of editorials for the last three years, it was found that the opinions for and against the privatization were equally matched according to the centrality analysis result. On the other hand, there is one noticeable result in centrality analysis, which is the keywords such as "US," "Korea US" and "FTA" showed centrality to some extent. It shows privatization is handled relating US and Korea US FTA by editorials.

• Journal of Digital Convergence
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• v.12 no.2
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• pp.343-351
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• 2014

The present study performed semantic network analysis of the keywords in the headlines of newspapers to investigate the media coverage of the multidrug-resistant microorganisms(MDROs) which is resistant to antibiotics. For this purpose, 229 news stories on MDROs in 28 newspapers from June 1, 2010 to December 31, 2011 were analyzed. The news stories were gathered from the Korea Press Foundation's news database, KINDS (www.kinds.or.kr) and websites of Korean newspapers. The analysis of the keywords revealed 'superbacteria' appeared most frequently (n=155) followed by 'infection' (n=63) which arouses fear among readers. While network was structured with the keywords such as 'domestic', 'multidrug-resistant microorganisms', 'first', 'antibiotics', 'outbreak' and 'infection', the keywords such as 'MDROs related stocks', 'medical staff', and 'safety' were on the periphery of the network.

• The Research Journal of the Costume Culture
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• v.27 no.3
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• pp.193-205
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• 2019

A trend analysis of research articles in a field of knowledge is significant because it can help in finding out the structural characteristics of the field and the future direction of research through observing change in a time series. We identified the structural characteristics and trends in text data (keywords) gathered from research articles which in itself is an important task in various research areas. The titles and keywords were crawled from research articles published from 2016 to 2018 in the Research Journal of the Costume Culture (RJCC), one of the representative Korean journal in the field of clothing and textile. After we extracted data comprising English titles and keywords from 195 published articles, we transformed it into a 1-mode matrix. We used measures from network analysis (i.e., link, strength, and degree centrality) for evaluating meaningful patterns and trends in the research on clothing and textile. NodeXL was used for visualizing the semantic network. This study observed change in the clothing and textile research trend. In addition to covering the core areas of the field, the subjects of research have been diversifying with every passing year and have evolved onto a developmental direction. The most studied area in articles published by the RJCC was fashion retailing/consumer psychology while aesthetic/historic and fashion industry/policy studies were covered to a more limited extent. We observed that most of the studies reflecting the identity of RJCC share subject keywords to a significant extent.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.1
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• pp.17-33
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• 2023

Disasters in coastal regions are a constant source of damage due to their uncertainty and complexity, leading to the proposal of green infrastructure as a nature-based solution that incorporates the concept of resilience to address the limitations of traditional grey infrastructure. This study analyzed trends in research related to coastal disasters and green infrastructure by conducting a co-occurrence keyword analysis of 2,183 articles collected from the Web of Science (WoS). The analysis resulted in the classification of the literature into four clusters. Cluster 1 is related to coastal disasters and tsunamis, as well as predictive simulation techniques, and includes keywords such as surge, wave, tide, and modeling. Cluster 2 focuses on the social system damage caused by coastal disasters and theoretical concepts, with keywords such as population, community, and green infrastructure elements like habitat, wetland, salt marsh, coral reef, and mangrove. Cluster 3 deals with coastal disaster-related sea level rise and international issues, and includes keywords such as sea level rise (or change), floodplain, and DEM. Finally, cluster 4 covers coastal erosion and vulnerability, and GIS, with the theme of 'coastal vulnerability and spatial technique'. Keywords related to green infrastructure in cluster 2 have been continuously appearing since 2016, but their focus has been on the function and effect of each element. Based on this analysis, implications for planning and management processes using green infrastructure in response to coastal disasters have been derived. This study can serve as a valuable resource for future research and policy in responding to and managing various disasters in coastal regions.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.5
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• pp.409-419
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• 2016

In general, Area studies have very flexible field of research, so it is very difficult to proceed all field of research at the same time. Due to this, researches on Area studies have been changed the field of research and research trends according to age. So it is important to identify research trends for performing Area studies. Also, interests for understanding the research trend of Area studies are increasing constantly. In this paper, we analyze research trends of Mediterranean Area studies in Korea by using co-appearance keywords. To do this, we first analyze article types and extract co-appearance keywords on articles of 『Journal of Mediterranean Area Studies』, which is the representative journal of Mediterranean region in Korea. In details, trends analysis of Mediterranean Area studies would be performed by using cp-keywords of article and visualizing network graph forms.