• Korean Journal of Health Education and Promotion
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• v.29 no.1
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• pp.1-11
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• 2012

Objectives: The nurse visiting health service named Customized Visiting Health Care Program(CVHCP) requires the service innovations incorporating community support into a local service network. The purpose of this study was to assess the community network in CVHCP and inform improvement in this network. Methods: We used Social Network Analysis(SNA) in one CVHCP at H city. Network links were generated by self-administered questionnaires by the 14 community resource centers who quantified their links to all other 25 agents on the list. Links were analyzed by a dichotomous scale for any experience of collaboration and a scored scale of 0 to 3 for level of collaboration using UCINET v6. Results: A list of 14 agents was generated, and local network was dominated by the Public Health Center and a local welfare center named Unlimited Care Center(UCC). According to centrality score, UCC was the most prominent agent, and Public Health Center was the most influential agent, being a link in the pathway flow between other agents for 9.5% of contribution. CVHCP scored lower rank of prominent with 30.8% of other agents reported referring to it. Conclusions: Social network analysis provides a useful network description for informing and evaluation service network improvement in maximizing its service for the CVHCP.

• Culinary science and hospitality research
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• v.23 no.8
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• pp.195-205
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• 2017

The purpose of this study was to compare the Starbucks in South Korea with Starbucks in U.S.A through the semantic network analysis of big data by collecting online data with SCTM(Smart Crawling & Text Mining) program which was developed by big data research institute at Kyungsung University, a data collecting and processing program. The data collection period was from January 1st 2014 to December 7th 2017, and packaged Netdraw along with UCINET 6.0 were utilized for data analysis and visualization. After performing CONCOR(convergence of iterated correlation) analysis and centrality analysis, this study illustrated the current characteristics of Starbucks for Korea and U.S.A reflected by the social network and the differences between Korea and U.S.A. Since the Starbucks was greatly developed, especially in Korea. this study also was supposed to provide significant and social-network oriented suggestions for Starbucks USA, Starbucks Korea and also the whole coffee industry. Also this study revealed that big data analytics can generate new insights into variables that have been extensively studied in existing hospitality literature. In addition, implications for theory and practice as well as directions for future research are discussed.

• Culinary science and hospitality research
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• v.24 no.2
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• pp.34-43
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• 2018

The objective of this study was to acquire a general and text-based awareness and recognition of cruise food hygiene through big data analytics. For the purpose, this study collected data with conducting the keyword "food hygiene, cruise" on the web pages and news on Google, during October 1st, 2015 to October 1st, 2017 (two years). The data collection was processed by SCTM which is a data collecting and processing program and eventually, 899 kb, approximately 20,000 words were collected. For the data analysis, UCINET 6.0 packaged with visualization tool-Netdraw was utilized. As a result of the data analysis, the words such as jobs, news, showed the high frequency while the results of centrality (Freeman's degree centrality and Eigenvector centrality) and proximity indicated the distinct rank with the frequency. Meanwhile, as for the result of CONCOR analysis, 4 segmentations were created as "food hygiene group", "person group", "location related group" and "brand group". The diagnosis of this study for the food hygiene in cruise industry through big data is expected to provide instrumental implications both for academia research and empirical application.

• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.5
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• pp.1019-1035
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• 2020

This study examines the millennial generation, who express themselves and share information on social media after experiencing constantly changing 'hot places' (places of interest) in contemporary cities, with the goal of analyzing space consumption behaviors. Data were collected via an Instagram crawler application developed with Python 3.4 administered to 19,262 posts using the term 'hot places' from November 1 and December 15, 2019. Issues were derived from a text mining technique using Textom 2.0; in addition, semantic network analysis using Ucinet6 and the NetDraw program were also conducted. The results are as follows. First, a frequency analysis of keywords for hot places indicated words frequently found in nouns were related to food, local names, SNS and timing. Words related to positive emotions felt in experience, and words related to behavior in hot places appeared in predicate. Based on importance, communication is the most important keyword and influenced all issues. Second, the results of visualization of semantic network analysis revealed four categories in the scope of the definition of "hot place": (1) culinary exploration, (2) atmosphere of cafés, (3) happy daily life of 'me' expressed in images, (4) emotional photos.

• Human Ecology Research
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• v.59 no.2
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• pp.245-259
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• 2021

The purpose of this study was to analyze big data to identify the sub-dimensions of ethical consumption, as well as the consumption value associated with ethical consumption that changes over time. For this study, data were collected from Naver and Daum using the keyword 'ethical consumption' and frequency and matrix data were extracted through Textom, for the period January 1, 2016, to December 31, 2018. In addition, a two-way mode network analysis was conducted using the UCINET 6.0 program and visualized using the NetDraw function. The results of text mining show increasing keyword frequency year-on-year, indicating that interest in ethical consumption has grown. The sub-dimensions derived for 2014 and 2015 are fair trade, ethical consumption, eco-friendly products, and cooperatives and for 2016 are fair trade, ethical consumption, eco-friendly products and animal welfare. The results of deriving consumption value keywords were classified as emotional value, social value, functional value and conditional value. The influence of functional value was found to be growing over time. Through network analysis, the relationship between the sub-dimensions of ethical consumption and consumption values derived each year from 2014 to 2018 showed a significantly strong correlation between eco-friendly product consumption and emotional value, social value, functional value and conditional value.

• Journal of Fashion Business
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• v.25 no.2
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• pp.110-126
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• 2021

This study aims to explore consumers' perception regarding "one-mile wear" and "home wear" fashion, an emerging trend during the Coronavirus disease (COVID-19) pandemic, and to identify the changes in consumers' perception of this style before and after the pandemic. The data collection period was set as one year before and after the outbreak as of January 1, 2020, and blog posts with keywords "one-mile wear" and "home wear" were collected. Further, textual data crawled and refined using Python 3.7 libraries, and centralities were measured and visualized through NodeXL 1.0.1 and Ucinet 6. According to the results, first, consumers' perception regarding one-mile wear fashion was divided into the following eight categories: wearing situation, expected attribute, style, item, color, textile, shape, and target wearer. Second, before the pandemic, home wear was recognized as pajamas or indoor wear; after the pandemic, home wear was recognized as one-mile wear, outdoor wear, and daily wear. Moreover, keywords, such as "telecommuting", "social distancing", "untact", and "upper body", appeared after the pandemic. It was confirmed that consumers' perception of home wear was affected by the pandemic.

• 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.

• Journal of Korean Society for Quality Management
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• v.52 no.2
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• pp.323-340
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• 2024

Purpose: The purpose of this study was to propose useful suggestions by analyzing research Xiaomi which are big data analyses, by collecting data based on Customer Perception in Textom. Methods: The collected data through scraping social media on the Textom site. And data preprocessing was performed using deleting and organizing data(text) that are duplicated, irrelevant, and where there is no meaning. The derived data were analyzed using Textom and Ucinet 6.0 with Text Analysis, WordClould, TF-IDF, Network Analysis, and Emotional analysis. Results: The results of this study are as follows; although the results of Xiaomi's text at domestic and global were similar, it was analyzed that there were perceptions of Xiaomi-related smart home products and cost-effectiveness in Korea, while in foreign countries, there were perceptions of functions and performance centered on smartphones. At domestic and global, the perception of Xiaomi was analyzed to be positive, and implications were presented based on these analysis results. Conclusion: Based on the results, if the product's performance or product competitiveness is considered to be meaningful in the market, and it is expected that there will be an opportunity to change the overall image of Chinese products.

• Journal of the Korean Society of Earth Science Education
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• v.11 no.2
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• pp.145-157
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• 2018

The purpose of this study is to analyze the research trends in domestic related to gifted counseling by utilizing Sementic analysis methods. For papers of gifted education in korea, KCI(Korea Citation Index) rated journals were selected 83 pieces published in journals were collected and the Sementic Network Analysis(SNA) way was utilizing for keyword frequency and Centrality Network Analysis throughout a variety of research articles using krkwic and Ucinet6.0. The results are as follows. first, the analysis appeared that the trends of paper keywords from highest frequency of appearance keyword in papers focused on four keywords: perfectionism, career, counseling, and the science gifted. second, Analysis of annual trends from 2001 to June 2018 showed that the top keywords were as follows: the gifted underachievers, the perfectionism, the gifted students of Science, and the science gifted students. the rising keywords were perfectionism, twice-exceptional students, and gifted parents, and the keywords of gifted students and general students showed a tendency to decrease. Consequently, gifted counseling research should be done from various perspectives.

• Journal of Fashion Business
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• v.23 no.5
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• pp.81-95
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• 2019

The purpose of this study is to research consumers' perception of the HiSeoul fashion show, which is being used by new designers as a means of promotion, and to propose a strategy for revitalizing new designer brands. This was done in order to secure basic data from fashion consumers, to help guide marketing strategies and promote rising designers. In this research, the consumers' perception of HiSeoul fashion show was verified using text-mining, data refinement and word clouding that was undertaken by TEXTOM3.0. Also, semantic network analysis, CONCOR analysis and visualization of the analysis results were performed using Ucinet 6.0 and NetDraw. "HiSeoul fashion show" was used as the keyword for text-mining and data was collected from March 1, 2018 to April 30, 2019. Using frequency analysis, TF-IDF, and N-gram, it was also shown that consumers are aware of places where shows are held, such as DDP and Igansumun. It was also revealed that consumers recognize rising designer brands, designer's names, the names of guests attending the show and the photo times. This study is meaningful in that it not only confirmed consumers' interest in new designer brands participating in the HiSeoul Fashion Show through big data but also confirmed that it is available as a marketing strategy to boost brand sales. This study suggests using HiSeoul show room to induce consumer sales, or inviting guests that match the brand image to promote them on SNS on the day the show is held for a marketing strategy.