• The Korean Journal of Franchise Management
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• v.14 no.3
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• pp.17-35
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• 2023

Purpose: As more and more food franchise companies want to expand overseas, related research is becoming more and more necessary. This study aims to examine the critical factors for successful overseas expansion according to the stages of overseas expansion, derive vital associations, and examine the success factors of overseas expansion through semantic network analysis. Research Design, Data, and Methodology: This study conducted in-depth interviews with three food franchise companies that have experienced overseas expansion and conducted semantic network analysis among crucial associations. The semantic network analysis was conducted using the Textom program. Results: Based on the results of the in-depth interview analysis, the factors considered when expanding overseas were categorized as 1) standardization and localization strategies of overseas franchisees, 2) physical environment of overseas franchisees, 3) entry types of overseas franchisees, 4) constraints of overseas franchisees, and 5) success criteria of overseas franchisees. The semantic network analysis based on the corresponding keywords showed that the importance of local partners is very high in common. Conclusion: This study examined and re-categorized the important factors to consider when a restaurant franchise company expands overseas in a step-by-step manner. In addition, an attempt was made to examine the keywords derived from the semantic network analysis objectively. The results provided theoretical and practical implications for the successful overseas expansion of franchise companies.

• Journal of Fashion Business
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• v.27 no.4
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• pp.115-124
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• 2023

This study reviewed hanbok terms emerging in academic research and media fields to conceptualize hanbok terms. Terms of hanbok were collected through RISS and Bigkinds by field. Results of textming using Textom were as follows. First, a total of 17 hanbok terms appeared in the field of academic research and a total of 41 hanbok terms appeared in the field of media, showing a difference. Fourteen terms, including hanbok, traditional hanbok, traditional clothing, daily hanbok, modernized hanbok, fashion hanbok, fusion hanbok, Shinhanbok, ready-made hanbok, luxury hanbok, women's hanbok, and children's hanbok, were hanbok terms that appeared in both academic and media fields. Second, the appearance of hanbok terms was examined based on five terms: traditional hanbok, daily hanbok, modernized hanbok, fusion hanbok, and Shinhanbok, which differed in the appearance of hanbok terms between academic research and media. Traditional hanbok and daily hanbok terms steadily appeared in both academic research and media, with modernized hanbok and fusion hanbok appearing mainly in the media and Shinhanbok in the academic research fields. Results of this studys confirmed that there were differences in terms of hanbok used between academic research and media fields.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.137-144
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• 2023

The purpose of this study is to examine consumers' perceptions of domestic infertility support policies based on infertility-related keywords and the trends of their changes. To this end, Momsholic, a mom cafe which has the most active infertility-related bulletin boards on Naver, was selected as the analysis target, and 'infertility' was selected as a keyword for data search. The data was collected for three months. In addition, network analysis and visualization were performed using R for data collection and analysis, and cross-validation was attempted using the NetDraw function of 'textom 1.0' and the UCINET6 program. As a result of the analysis, the main keywords were cost, artificial insemination, in vitro fertilization, freezing, harvest, ovulation, and how much. Next, looking at the central value of the degree of connection, it was found that the degree of connection between the words cost, cost, how much, problem, public health center, and artificial insemination was high. According to the results of this study, women who visit mom cafes due to infertility in Korea are more interested in the cost. It is believed to be closely related to infertility treatment as well as in vitro fertilization and egg freezing. Therefore, by examining keywords related toinfertility, it has academic significance in that it is possible to identify major factors that end users are interested in. Furthermore, it is possible to redefine the guidelines for domestic infertility support policies by presenting infertility support policies that reflect the factors of interest of end consumers.

• Fashion & Textile Research Journal
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• v.25 no.1
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• pp.72-81
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• 2023

As changes in social and economic paradigms are accelerating, and non-contact has become the new normal due to the COVID-19 pandemic, metaverse services that build societies in online activities and virtual reality are spreading rapidly. This study analyzes the perception and trend of metaverse fashion using big data. TEXTOM was used to extract metaverse and fashion-related words from Naver and Google and analyze their frequency and importance. Additionally, structural equivalence analysis based on the derived main words was conducted to identify the perception and trend of metaverse fashion. The following results were obtained: First, term frequency(TF) analysis revealed the most frequently appearing words were "metaverse," "fashion," "virtual," "brand," "platform," "digital," "world," "Zepeto," "company," and "game." After analyzing TF-inverse document frequency(TF-IDF), "virtual" was the most important, followed by "brand," "platform," "Zepeto," "digital," "world," "industry," "game," "fashion show," and "industry." "Metaverse" and "fashion" were found to have a high TF but low TF-IDF. Further, words such as "virtual," "brand," "platform," "Zepeto," and "digital" had a higher TF-IDF ranking than TF, indicating that they had high importance in the text. Second, convergence of iterated correlations analysis using UNICET revealed four clusters, classified as "virtual world," "metaverse distribution platform," "fashion contents technology investment," and "metaverse fashion week." Fashion brands are hosting virtual fashion shows and stores on metaverse platforms where the virtual and real worlds coexist, and investment in developing metaverse-related technologies is under way.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.5
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• pp.804-821
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• 2023

This study examines current trends and perceptions of veganism and vegan fashion in Korea, China, and the United States. Using big data tools Textom and Ucinet, we conducted cluster analysis between keywords. Further, frequency analysis using keyword extraction and CONCOR analysis obtained the following results. First, the nations' perceptions of veganism and vegan fashion differ significantly. Korea and the United States generally share a similar understanding of vegan fashion. Second, the industrial structures, such as products and businesses, impacted how Korea perceived veganism. Third, owing to its ongoing sociopolitical tensions, the United States views veganism as an ethical consumption method that ties into activism. In contrast, China views veganism as a healthy diet rather than a lifestyle and associates it with Buddhist vegetarianism. This perception is because of their religious history and culinary culture. Fundamentally, this study is meaningful for using big data to extract keywords related to vegan fashion in Korea, China, and the United States. This study deepens our understanding of vegan fashion by comparing perceptions across nations.

• Korean Journal of Childcare and Education
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• v.20 no.1
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• pp.91-111
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• 2024

Objective: The purpose of this study is to explore trends in institutional evaluation research in early childhood education through keyword network analysis. This aims to understand trends in academic discourse on institutional evaluation and gain implications for follow-up research and related policy directions. Methods: A total of 6,629 keywords were extracted from 572 dissertations and journal articles published from January 2006 to October 2023 for the purpose of analyzing and visualizing the frequency and centrality of keywords, as well as the structural properties of keyword networks. The analysis and visualization were conducted using the TEXTOM, UCINET6, and NetDraw programs. Results: First, the number of institutional evaluation studies increased steadily from 2006 to 2010 and then decreased, with a higher frequency of studies on daycare centers compared to kindergartens. Second, the most frequently occurring keyword in the analysis was 'daycare center,' and the highest connection strength was found in the term 'daycare-center-evaluation.' Third, network analysis revealed that key terms for institutional evaluation research included 'evaluation certification,' 'recognition,' 'evaluation indicators,' 'teacher,' 'daycare center,' and 'kindergarten.' In the ego network analysis for each institution, 'parent' emerged as a highly ranked keyword. Conclusion/Implications: This study confirmed the perspectives of previous studies by revealing the structure of core concepts in early childhood education institution evaluation research, and provided implications for follow-up and direction of institution evaluation

• Journal of Korean society of Dental Hygiene
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• v.23 no.6
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• pp.451-458
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• 2023

Objectives: The purpose of this study is to explore the research trends of elderly oral health through a language network analysis. Methods: A total of 354 published studies with 668 keywords were collected from the Research Information Sharing Service (RISS) between 2000 and 2022. Language network analysis was performed using Textom 6.0, Ucinet 6.774, and NetDraw 2.183. Results: The most frequent keywords were 'elderly', 'oral health', 'quality of life', and 'OHIP-14'. The result of frequency-inverse document frequent keywords showed similar results to the most frequent keywords. The N-gram of keywords shows that 'elderly', 'oral health' (18 times) and 'elderly', 'depression' (7 times). As a results of the analysis of degree centrality and between centrality, 'elderly', 'oral health', and 'quality of life' were found to be high. The CONCOR analysis identified the main clusters of 'quality of life', 'oral health behavior', 'health', and 'oral function disorder'. Conclusions: The results of the current study could be available to know research trends in elderly oral health and it is necessary to improve more comprehensive study in follow-up study.

• International Journal of Advanced Culture Technology
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• v.12 no.1
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• pp.270-275
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• 2024

Introduction. In this study, purpose is to analize the types of golf tourism, inbound or outbound, by using big data and see how movement of industry is being changed and what changes have been made during and after Covid-19 in golf industry. Method Using Textom, a big data analysis tool, "golf tourism" and "Covid-19" were selected as keywords, and search frequency information of Naver and Daum was collected for a year from 1 st January, 2023 to 31st December, 2023, and data preprocessing was conducted based on this. For the suitability of the study and more accurate data, data not related to "golf tourism" was removed through the refining process, and similar keywords were grouped into the same keyword to perform analysis. As a result of the word refining process, top 36 keywords with the highest relevance and search frequency were selected and applied to this study. The top 36 keywords derived through word purification were subjected to TF-IDF analysis, visualization analysis using Ucinet6 and NetDraw programs, network analysis between keywords, and cluster analysis between each keyword through Concor analysis. Results By using big data analysis, it was found out option of oversea golf tourism is affecting on inbound golf travel. "Golf", "Tourism", "Vietnam", "Thailand" showed high frequencies, which proves that oversea golf tour is now the re-coming trends.

• Journal of the Korean Society of Clothing and Textiles
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• v.48 no.4
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• pp.729-743
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• 2024

This research explores consumer preferences for materials in different clothing product categories, using web-crawling and text mining techniques. Specifically, the study focuses on the material-related terms found in consumer reviews across three distinct product categories: functional clothing, formal shirts, and knit sweaters. Top-selling products within each category were identified on the Naver Shopping website based on the volume of reviews, and the four most-reviewed products were selected. Six hundred reviews per product were analyzed using the Textom big-data analysis software to determine the frequency of material-related mentions and word associations. The analysis utilized two comparative metrics: product category and usage duration. Our findings reveal notable variations in the material preferences mentioned by consumers across different product categories. The study suggests a need to re-evaluate existing standardized review criteria to better reflect consumer interests specific to each product category. Additionally, an increase in material-related terms in reviews over one month indicates the potential importance of extending the duration of product reviews to enhance the accuracy of information that reflects longer-term consumer experiences with material quality.

• The Research Journal of the Costume Culture
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• v.28 no.2
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• pp.265-284
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• 2020

This study aimed to analyze the performance of Disney-collaborated fashion lines based on online consumer reviews. To do so, the researchers employed text mining and network analysis to identify key words in the reviews of these products. Blogs, internet cafes, and web documents provided by Naver, Daum, and YoutTube were selected as subjects for the analysis. The analysis period was limited to one year after for the 2019. Data collection and analysis were conducted using Python 3.7, Textom, and NodeXL. The research terms in question were as follows: 'Disney fashion collaboration' and 'Frozen fashion collaboration'. Preliminary survey results indicated that 'Elsa's dress' was the most frequently mentioned term and that the domestic fashion brand Eland Retail was the most active in selling Disney branded clothing through its own brand. The writers of reviews for Disney-collaborated fashion products were primarily mothers with daughters. Their decision to purchase these products was based upon the following factors; price, size, stability of decoration, shipping, laundry, and retailer. The motives for purchasing the product were the positive response of the consumer's child and the satisfaction of the parents due to the child's response. The problems to be solved included insufficient quantity of supply, delay in delivery, expensive price considering the number of times children's clothes are worn, poor glitter decoration, faded color, contamination from laundry, and undesirable smells immediately after the purchase.