• 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.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.79-88
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• 2022

Social media big data includes a lot of information that can identify not only consumer consumption patterns but also local images. This paper was collected annually data including 'Samcheok' from 2015 to 2019 from Blog and Cafe of Naver and Daum in domestic portal site, and analyzed the regional image change after refining keyword which forms the regional image by performing text mining and network analysis. According to the research results, the regional image of 2015 was expressed with image cognitive elements of the nearby place name or place etc. such as 'Jangho Port', 'Donghae', and 'Beach'. However the regional image both 2016 and 2019 were changed with image cognitive elements of 'SamcheokSolbich' which is a special place within region. Therefore as the keywords related to the local image include 'Jangho Port' and Resort, which are the representative attractions of Samcheok, it can be seen that the infrastructure factor plays a big role in forming the local image. The significance test for the network data used the bootstrap technique, and the p-values in 2015, 2016, and 2019 were 0.0002, 0.0006, and 0.0002, respectively, which were found to be statistically significant at the significance level of 5%.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.193-204
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• 2022

The 2018 Seoul Zero Pay is a policy actively promoted by the government as an economic stimulus package for small business owners and the self-employed who are experiencing economic depression due to COVID-19. However, the controversy over the effectiveness of Zero Pay continues even after two years have passed since the implementation of the policy. Zero Pay is a joint QR code mobile payment service introduced by the government, Seoul city, financial companies, and private simple payment providers to reduce the burden of card merchant fees for small business owners and self-employed people who are experiencing economic difficulties due to the economic downturn., it was attempted in the direction of economic revitalization for the return of alleyways[1]. Therefore, this study intends to draw implications for improvement measures so that the ongoing zero-pay can be further activated and the economy can be settled normally. The analysis results of this study are as follows. First, it shows the effect of increasing the income of small business owners by inducing consumption in alleyways through the economic revitalization policy of Zero Pay. Second, the issuance and distribution of Zero Pay helps to revitalize the local economy and contribute to the establishment of a virtuous cycle system. Third, stable operation is being realized by the introduction of blockchain technology to the Zero Pay platform. In terms of academic significance, the direction of Zero Pay's policies and systems was able to identify changes in the use of Zero Pay through big data analysis. The implementation of the zero-pay policy is in its infancy, and there are limitations in factors for examining the consumer image perception of zero-pay as there are insufficient prior studies. Therefore, continuous follow-up research on Zero Pay should be conducted.

• Journal of the FoodService Safety
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• v.4 no.1
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• pp.35-41
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• 2023

This study was based on the results of the study of 'Cheonyeon and Chunghyun Taste Alley Pilgrimage- Introducing Hidden Restaurants in Our Town', which was adopted as a project to revitalize urban regeneration as part of the Cheonyeon and Chunghyun Urban Regeneration New Deal project. This study was conducted in total of two stages, as a first step, the commercial district of Seodaemun Station was analyzed by analyzing the hashtag (#) mentioned along with the "Seodamun Station Restaurant" on Instagram from 2015 to 2020. As a result of the analysis, it was found to be an office commercial district related to "office workers", and it was found to be a commercial district with the characteristics of "small but certain happiness" where you can find hidden restaurants in front of your house. Based on the characteristics of these commercial districts, five stores utilizing the characteristics of the region were selected and cooking classes were conducted for students of Kyonggi University, who are local residents. The purpose of this study was to revitalize the aging Seoul city and contribute to the formation of positive relationships between local residents and merchants through cooking classes. In addition, the process was produced as digital media content and used as local promotional materials.

• The Journal of Korean Obstetrics and Gynecology
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• v.37 no.3
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• pp.20-32
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• 2024

Objectives: The purpose of this study is to investigate the domestic awareness of Korean medicine treatment for dysmenorrhea. Methods: We conducted word frequency analysis, 2-gram analysis, degree centrality analysis, and CONCOR analysis using big data searched for '월경통', '생리통', and '한방' as main key words. The searching period was set from 2019 to 2023. Results: The number of original text data searched through main key words was on the rise. Specific words related to Korean medicine treatment were in the top 100, words related to herbal medicine ranked particularly high. The top 100 words were divided into 4 clusters (A; Body parts or body substances related to dysmenorrhea, B; Symptoms that accompany dysmenorrhea, C; Physiological or pathological situations related to dysmenorrhea, and D; Treatment related words of dysmenorrhea) and some clusters showed close relationships between each others (B-C, B-D, and C-D). Conclusions: Our results suggest that interest in Korean medicine treatment for dysmenorrhea is increasing. Also, as public understanding is estimated to be high, specific information such as method, process and mechanism of Korean medicine treatment seems to be needed.

• Journal of the Korea Society of Computer and Information
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• v.29 no.9
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• pp.225-236
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• 2024

This study focuses on Xiaomi, which has gained attention amid the Fourth Industrial Revolution. Using Textom, customer perceptions of Xiaomi were collected over approximately 10 years and analyzed. Data from 2015 to 2023 were used to compare customer perceptions in South Korea and China. The analysis revealed that before 2016, both countries focused on Xiaomi as a company and its basic products. However, after 2016, perceptions shifted to include keywords related to expansion products. Additionally, perceptions of Xiaomi were positive in both countries, with South Korea showing an increasing positivity, while China maintained positive views. This suggests that entry barriers for Xiaomi in the domestic market have decreased significantly. Future research should involve big data analysis and comparative studies with other countries for more objective insights.

• Journal of Fashion Business
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• v.25 no.3
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• pp.90-107
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• 2021

This study concludes that communication based on interaction between broadcasting hosts and consumers is differently characterized by fashion live commerce types. Subcategories of the types of fashion live commerce were created and used in the analyses of domestic consumer awareness. Three subcategories were created: The department store type, Designer brand type, and Influencer host type. Comments representing consumers' awareness that appear immediately during real-time broadcasting were collected and used for the analyses. The frequency and TF-IDF-based top keywords were selected to analyze the semantic network and CONCOR, and the top keywords were analyzed by deriving the values of degree of centrality. The analysis identified that a group of product attributes and a group of live commerce offered value were common between the three types. As for the group characteristics classified by type, for the department store types, brand attributes, benefits, and values from pursuing the products were identified. For designer brand types, a group of viewers' responses and inquiries were identified. It is interpreted that the satisfaction value gained from hosts with product expertise has been clustered. Influencer host types have affirmed a group of external product values. A close relationship is formed and it is thought to have led a group of values to trust the external image of the product. This study carries significance in analyzing real-time comment data from consumers using fashion live commerce to empirically reveal the characteristics of each type.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.113-123
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• 2020

In this paper, big data analysis was conducted for past and present fashion trends and fashion cycle. We focused on daily look for ordinary people instead of the fashion professionals and fashion show. Using the social matrix tool, Textom, we performed frequency analysis, N-gram analysis, network analysis and structural equivalence analysis on the big data containing fashion trends and cycles. The results are as follows. First, this study extracted the major key words related to fashion trends for the daily look from the past(1980s, 1990s) and the present(2019 and 2020). Second, the frequence analysis and N-gram analysis showed that the fashion cycle has shorten to 30-40 years. Third, the structural equivalence analysis found the four representative clusters. The past four clusters are jean, retro codi, athleisure look, celebrity retro and the present clusters are retro, newtro, lady chic, retro futurism. Fourth, through the network analysis and N-gram analysis, it turned out that the past fashion is reproduced and evolves to the current fashion with certain reasoning.

• Journal of Korea Entertainment Industry Association
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• v.14 no.6
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• pp.139-150
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• 2020

The data processing of this study focuses on the textom and social media words about three areas: 'Corona 19 and professional baseball', 'Corona 19 and professional baseball', and 'Corona 19 and professional sports' The data was collected and refined in a web environment and then processed in batch, and the Ucinet6 program was used to visualize it. Specifically, the web environment was collected using Naver, Daum, and Google's channels, and was summarized into 30 words through expert meetings among the extracted words and used in the final study. 30 extracted words were visualized through a matrix, and a CONCOR analysis was performed to identify clusters of similarity and commonality of words. As a result of analysis, the clusters related to Corona 19 and Pro Baseball were composed of one central cluster and five peripheral clusters, and it was found that the contents related to the opening of professional baseball according to the corona 19 wave were mainly searched. The cluster related to Corona 19 and unrelated to professional baseball consisted of one central cluster and five peripheral clusters, and it was found that the keyword of the position of professional baseball related to the professional baseball game according to Corona 19 was mainly searched. Corona 19 and the cluster related to professional sports consisted of one central cluster and five peripheral clusters, and it was found that the keywords related to the start of professional sports according to the aftermath of Corona 19 were mainly searched.

• The Journal of Industrial Distribution & Business
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• v.12 no.1
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• pp.47-62
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• 2021

Purpose: Our purpose in this study was to examine the strategies for the development of watermelon industry using unstructured big data analysis. That is, this study was to look the change of issues and consumer's perception about watermelon using big data and social network analysis and to investigate ways to strengthen the competitiveness of watermelon industry based on that. Methodology: For this purpose, the data was collected from Naver (blog, news) and Daum (blog, news) by TEXTOM 4.5 and the analysis period was set from 2015 to 2016 and from 2017-2018 and from 2019-2020 in order to understand change of issues and consumer's perception about watermelon or watermelon industry. For the data analysis, TEXTOM 4.5 was used to conduct key word frequency analysis, word cloud analysis and extraction of metrics data. UCINET 6.0 and NetDraw function of UCINET 6.0 were utilized to find the connection structure of words and to visualize the network relations, and to make a cluster of words. Results: The keywords related to the watermelon extracted such as 'the stalk end of a watermelon', 'E-mart', 'Haman', 'Gochang', and 'Lotte Mart' (news: 015-2016), 'apple watermelon', 'Haman', 'E-mart', 'Gochang', and' Mudeungsan watermelon' (news: 2017-2018), 'E-mart', 'apple watermelon', 'household', 'chobok', and 'donation' (news: 2019-2020), 'watermelon salad', 'taste', 'the heat', 'baby', and 'effect' (blog: 2015-2016), 'taste', 'watermelon juice', 'method', 'watermelon salad', and 'baby' (blog: 2017-2018), 'taste', 'effect', 'watermelon juice', 'method', and 'apple watermelon' (blog: 2019-2020) and the results from frequency and TF-IDF analysis presented. And in CONCOR analysis, appeared as four types, respectively. Conclusions: Based on the results, the authors discussed the strategies and policies for boosting the watermelon industry and limitations of this study and future research directions. The results of this study will help prioritize strategies and policies for boosting the consumption of the watermelon and contribute to improving the competitiveness of watermelon industry in Korea. Also, it is expected that this study will be used as a very important basis for agricultural big data studies to be conducted in the future and this study will offer watermelon producers and policy-makers practical points helpful in crafting tailor-made marketing strategies.