• Journal of Korean Society for Quality Management
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• v.47 no.3
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• pp.597-613
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• 2019

Purpose: The purpose of this study is to analyze the trend of quality research by analyzing the entire JKSQM(Journal of the Korean Society for Quality Management). Methods: This study is to analyze the frequency of words used in the abstract of the all JKSQM by applying the text mining processing. We use wordcrowd among text mining techniques. Results: 22 words of high frequency were presented in the abstract of the paper published in the JKSQM for 42 years. The frequency of words was shown on a 10 year basis, and the four important words were plotted on a change graph for each Vol. Frequent words of each Vol. are added in the appendix. Conclusion: The main research results are as follows. First, there has been no significant change in research trends over the last 40 years. Second, the early SQC words have been widely used, and since 1990, many words such as service-oriented words have been used, indicating a change in the times. Third, the use of the words of the 4th industrial revolution since 2010 is weak. In the above analysis, the trend of quality research in Korea is within the quality category and can be considered conservative. Now, it is expected that everything will be changed in the period of the 4th Industrial Revolution, and it is time to study the direction of quality in Korea.

• Communications of Mathematical Education
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• v.32 no.4
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• pp.555-573
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• 2018

The purpose of this study is to identify the emotional language of math teachers in math class using text mining techniques. For this purpose, we collected the discourse data of the teachers in the class by using the excellent class video. The analysis of the extracted unstructured data proceeded to three stages: data collection, data preprocessing, and text mining analysis. According to text mining analysis, there was few emotional language in teacher's response in mathematics class. This result can infer the characteristics of mathematics class in the aspect of affective domain.

• The Journal of Information Systems
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• v.30 no.2
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• pp.189-214
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• 2021

Purpose This paper aims to effectively utilize user-generated content (UGC) and analyze the market structure of a relatively new market which lacks rich user review information. Specifically, we propose a domain-specific text mining tool for the domestic craft beer market and visualize the market structure by incorporating how individual beer products are positioned in the perceptual map of consumers. Design/methodology/approach We collect user review information from Naver blogs, and extract words that describe beers. We identify semantic relationships between beer products through text mining, and then depending on these semantic relationships, construct a graph representing the market structure of the domestic craft beer market based on the consumer's perceptual map. Findings First, beer products produced in the same brewery are perceived as very similar to consumers. Second, only two products, 'Heukdang Milky Stout' and 'Gompyo', was noticeably distinguishable from other products. Third, even though 'Gyeongbokgung' is from a different brewery, it is located very close to the products of 'Jeju Beer' brewery such as 'Jeju Baeknokdam Ale' and 'Seongsan Ilchulbong Ale', which suggests the influence of 'landmark series.' We successfully show that our methodology effectively describes the market structure of the craft beer market.

• Fashion & Textile Research Journal
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• v.24 no.5
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• pp.545-556
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• 2022

To overcome the pandemic, a new strategy for innovation is in demand throughout the value chains of the fashion industry that emphasize the importance of fashion technology. Accordingly, as various viewpoints and fields of debate are unfolding to consider the direction of change led by fashion technology, it is necessary to make an active value judgment precedent by understanding the differences between various opinions. This study aims to derive keywords from fashion technology used during the pandemic, to infer the characteristics of each type of perspective and to understand their characteristics. For the research, this study combines text mining analysis and content analysis. Text mining analysis is used to find statistical patterns by collecting keywords from big data from online media, and content analysis is used to interpret the data qualitatively. After analyzing the results of this study, the following observations are made. First, the perspective of positive acceptance seeks to maximize the perception and sensory action of fashion through technology; this amplifies experience, an opportunity for innovation and efficiency. Second, critical vigilance highlights the side effects of radical changes in fashion technology, characterized by concerns about capital-centered polarization, threats to human rights, and infringement of creative thinking. Lastly, the perspective of gradual adoption is the gradual convergence of technologies, characterized by the pursuit of an appropriate balance.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.1
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• pp.116-131
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• 2022

This study used text mining to analyze big data to understand consumers' demand for and perceptions of fashion masks. Based on the text-mining analysis results, a survey was conducted with those living in Korea to investigate the influence of consumers' mask selection criteria on mask brand awareness and purchase intention for fashion masks. "Fashion mask" and "functional mask" were used as the keywords in a text-mining analysis, and an online survey of 242 respondents was conducted. The analysis results were as follows: First, the text-mining analysis extracted commonly appearing words that had a high frequency and TF-IDF, such as "COVID-19," "fashion," "celebrity," "antibacterial," and "filter." This confirmed that during the COVID-19 pandemic, consumers have demanded masks that are both functional and fashionable. Second, among consumers' mask selection criteria, trend and design had positive effects on face-mask brand awareness. Third, face-mask brand awareness had a positive effect on the purchase intention for both brand and fashion masks, and the purchase intention for brand masks had a positive effect on the purchase intention for fashion masks.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.529-536
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• 2023

The secondhand market in Korea has been showing steady growth. However, the number of fraud cases and the amount of damages from fraudulent activities in secondhand transactions are also increasing. As of 2021, the size of the secondhand market reached 24 trillion won, but the total amount of fraud-related damages reached 360.6 billion won. In order to prevent fraud between individuals, secondhand trading platforms have implemented a safety payment system. However, new types of fraud methods exploiting the safety payment system have emerged, undermining the security of secondhand transaction safety payments. In this study, we aim to utilize text mining to examine the current state of the safety payment system in secondhand transactions and propose improvement measures by analyzing the system through text mining and network analysis.

• Journal of Fashion Business
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• v.27 no.5
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• pp.78-92
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• 2023

Fashion trends are actively disseminated through social media, which influences both their propagation and consumption. This study explored how users perceive subversive basic fashion in social media videos, by examining the associated concepts and characteristics. In addition, the factors contributing to the style's social media dissemination were identified and its distinctive features were analyzed. Through text mining analysis, 80 keywords were selected for semantic network and CONCOR analysis. TF-IDF and N-gram results indicate that subversive basic fashion involves transformative design techniques such as cutting or layering garments, emphasizing the body with thin fabrics, and creating bold visual effects. Topic modeling suggests that this fashion forms a subculture that resists mainstream norms, seeking individuality by creatively transforming the existing garments. CONCOR analysis categorized the style into six groups: forward-thinking unconventional fashion, bold and unique style, creative reworking, item utilization and combination, pursuit of easy and convenient fashion, and contemporary sensibility. Consumer actions, linked to social media, were shown to involve easily transforming and pursuing personalized styles. Furthermore, creating new styles through the existing clothing is seen as an economic and creative activity that fosters network formation and interaction. This study is significant as it addresses language expression limitations and subjectivity issues in fashion image analysis, revealing factors contributing to content reproduction through user-perceived design concepts and social media-conveyed fashion characteristics.

• Journal of the Korean Wood Science and Technology
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• v.51 no.6
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• pp.458-469
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• 2023

Text mining techniques provide valuable insights into research information across various fields. In this study, text mining was used to identify research trends in wood science from 2012 to 2022, with a focus on representative journals published in Korea and Japan. Abstracts from Journal of the Korean Wood Science and Technology (JKWST, 785 articles) and Journal of Wood Science (JWS, 812 articles) obtained from the SCOPUS database were analyzed in terms of the word frequency (specifically, term frequency-inverse document frequency) and co-occurrence network analysis. Both journals showed a significant occurrence of words related to the physical and mechanical properties of wood. Furthermore, words related to wood species native to each country and their respective timber industries frequently appeared in both journals. CLT was a common keyword in engineering wood materials in Korea and Japan. In addition, the keywords "MDF," "MUF," and "GFRP" were ranked in the top 50 in Korea. Research on wood anatomy was inferred to be more active in Japan than in Korea. Co-occurrence network analysis showed that words related to the physical and structural characteristics of wood were organically related to wood materials.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.13-19
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• 2024

Purpose: This study provides prevention methods by type of construction disaster using text mining techniques. Method: Based on the database that analyzed the cases of critical disasters in the domestic construction sector, preventive measures and causes are analyzed by text mining techniques, and the contents of the analysis are visually shown. Result: This visual data represents the measures for preventing critical disasters of each process according to the importance. Conclusion: It is believed that the results will be helpful in identifying factors to be considered in preparing preventive measures for serious accidents in construction.

• Korean Journal of Childcare and Education
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• v.20 no.4
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• pp.59-76
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• 2024

Objective: The purpose of this study is to explore research trends in creativity education for Korean children using term-frequency analysis, semantic network analysis, and topic analysis within text mining techniques. Methods: For this purpose, keywords were extracted from 802 articles published in KCI-listed journals from 2001 to 2022, using Textom. Results: This results showed that, first, words such as 'young children', 'creativity', 'activity', 'program', 'creative', 'test', 'education', and 'effectiveness' consistently appeared among the top 30 most frequent terms across all periods. Second, semantic network analysis revealed that while words like 'young children', 'creativity', 'activity', and 'program' consistently exhibited high centrality, there were notable changes in the centrality of 'test' over time, including a decrease in its centrality and varying influential words across different periods. Third, three to four topics were identified for each period, with common themes such as the effectiveness of programs to promote creativity in early childhood education, alongside period-specific topics like giftedness and play, highlighting the unique characteristics of each time period. Conclusion/Implications: This study provides insights into the research trends in early childhood creativity education over the past 22 years using text mining techniques and offers suggestions for future research directions.