• Journal of Environmental Impact Assessment
• /
• v.25 no.4
• /
• pp.296-306
• /
• 2016

There is a growing interest in establishing a regional climate change adaptation policy as the climate change impact in the region and local scale increases. This study focused on the analysis of 32 regions on its characteristics of local climate change adaptation plans. First, statistic program R was used for conducting cluster analysis based on the frequency and budgets of adaptation plan. Further, we analyzed damage frequency from newspapers regarding climate change impacts in eight categories which were caused by extreme weather events on 2,565 cases for 24 years. Lastly, the characteristics of climate change adaptation plan was compared with damage frequency patterns for evaluating the adequacy of climate change adaptation plan on each cluster. Four different clusters were created by cluster analysis. Most clusters clearly have their own characteristics on certain sectors. There was a high frequency of damage in 'disaster' and 'health' sectors. Climate change adaptation plan and budget also invested a lot on those sectors. However, when comparing the relative rate among regional governments, there was a difference between types of damage and climate change adaptation plan. We assumed that the difference could come from that each region established their adaptation plans based on not only the frequency of damage, but vulnerability assessment, and expert opinions as well. The result of study could contribute to policy making of climate change adaptation plan.

• Culinary science and hospitality research
• /
• v.24 no.3
• /
• pp.167-176
• /
• 2018

In this study, Big Data was used to collect the information related to 'Cooking Academy' keywords. After collecting all the data, we calculated the frequency through the text mining and selected the main words for future data analysis. Data collection was conducted from Google Web and News during the period from January 1, 2013 to December 31, 2017. The selected 64 words were analyzed by using UCINET 6.0 program, and the analysis results were visualized with NetDraw in order to present the relationship of main words. As a result, it was found that the most important goal for the students from cooking school is to work as a cook, likewise to have practical classes. In addition, we obtained the result that SNS marketing system that the social sites, such as Facebook, Twitter, and Instagram are actively utilized as a marketing strategy of the institute. Therefore, the results can be helpful in searching for the method of utilizing big data and can bring brand-new ideas for the follow-up studies. In practical terms, it will be remarkable material about the future marketing directions and various programs that are improved by the detailed curriculums through semantic network of cooking school by using big data.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.17 no.1
• /
• pp.3-10
• /
• 1993

This study intends to provide a beneficial foundation which can aid our understanding of how a clothing consumer group can be classified according to the clothing buying motives, and what differences are there about the importances store image attribute among them and how consumer's preferences to the store image are shown differently among them and ultimately, some concrete data which can be useful in establishing efficient store image strategies for clothing stores. 484 subjects were gathered through convenience sampling method and, for data analysis, cronbach' ${\alpha}$, frequency, percentage, mean, ${\chi}^2$-text, t-test, ANOVA, Duncan Multiple Range Test, Factor Analysis, Cluster Analysis were conducted. the results are as follows; 1. three kind of factors in the clothing buying motives were determined for analysis of consumers group and by which it was revealed as to be significant for us to classify them three subdivisions; those of fashion pursuit group, self display group, financial utilitarian group. 2. Importance on store image attribute was revealed that Ewha students regarded quality, price, more important factors than others. 3. Store image preferences show significantly when concerned with quality, price, fashion, impression and age of store personnel, convenience for exchanging and returning goods, credit, delivery and repair, mailing of catalogue and discount coupon, bightness of store among consumer groups.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.42 no.3
• /
• pp.428-437
• /
• 2018

This study derives evaluation terms by analyzing the semantic relationship between design elements and sentiment terms in regards to fashion design. As for research methods, a total of 38,225 texts from Daum and Naver Blogs from November 2015 to October 2016 were collected to analyze the parts, frequency, centrality and semantic networks of the terms. As a result, design elements were derived in the form of a noun while fashion image and user's emotional responses were derived in the form of adjectives. The study selected 15 noun terms and 52 adjective terms as evaluation terms for men's striped shirts. The results of semantic network analysis also showed that the main contents of the users of men's striped shirts were derived as characteristics of expression, daily wear, formation, and function. In addition, design elements such as pattern, color, coordination, style, and fit were classified with evaluation results such as wide, bright, trendy, casual, and slim.

• The Korean Journal of Health Service Management
• /
• v.12 no.3
• /
• pp.13-26
• /
• 2018

Objectives: This study investigated how Korean daily newspapers frame the present government's health insurance coverage expansion policy, Moon Jae-in Care. Methods: A contents analysis was conducted to construct news frames represented in the four Korean daily newspapers' editorials and columns on Moon Jae-in Care during from April 2017 to April 2018. News text was classified into three different layers of frames: expressive element, narrative structure, and implied values. Results: The analysis revealed that the frequency of narrative frames was as follows: health system improvement (20.8%), public burden (14.6%), opposition by doctors (14.6%), and populism (12.5%). The financial sustainability accounted for 41.7% of the value frame, followed by procedural legitimation (18.8%), and coverage expansion (16.7%). The results also revealed that reported frames were different among newspapers: Chosun Ilbo tended to report in a negative tone, while Hankyoreh shinmun and Kyunghyang shinmun used a positive tone. Conclusions: This finding suggests that there are salient framings in reports on Moon Jae-in Care. Based on the results, the government needs to present a detailed financing plan on Moon Jae-in Care in detail. I discussed another implication of media frames results.

• International Journal of Internet, Broadcasting and Communication
• /
• v.14 no.2
• /
• pp.206-211
• /
• 2022

As the level of consumption is improved and cultural life is pursued, the consumer's consciousness structure is rapidly changing, and the demand for product selection level, variety, and quality is becoming more diverse. The restaurant economy is falling due to the prolonged COVID-19, the economic recession, income decline, and changes in population structure and lifestyle, but the Meal- kit market is growing rapidly. This study aims to identify the consumer perception of Meal-kit, which is rapidly growing as an alternative to existing meals in the fields of dining out, food, and distribution due to the development of technology and social environment using big data. As a result of the analysis, the keywords with the highest frequency of appearance were in the order of Meal-kit, Cooking, Product, Launching, and Market and were divided into 8 groups through the CONCOR analysis. We want to identify consumer trends related to the key keywords of Meal-kit, present effective data related to Meal-kit demand for Meal-kit specialized companies, and provide implications for establishing marketing strategies for differentiated competitive advantage.

• Journal of People, Plants, and Environment
• /
• v.24 no.4
• /
• pp.415-427
• /
• 2021

Background and objective: This study examined the changes in the cultural trend of use for green infrastructure in Seoul due to COVID-19 pandemic. Methods: The subjects of this study are 8 sites of green infrastructure selected by type: Forested green infrastructure, Watershed green infrastructure, Park green infrastructure, Walkway green infrastructure. The data used for analysis was blog posts for a total of four years from August 1, 2016 to July 31, 2020. The analysis method was conducted keyword frequency analysis, topic modeling, and related keyword analysis. Results: The results of this study are as follows. First, the number of posts on green infrastructure has increased since COVID-19, especially forested green infrastructure and watershed green infrastructure with abundant naturalness and high openness. Second, the cultural trend keywords before and after COVID-19 changed from large-scale to small-scale, community-based to individual-based activities, and nondaily to daily culture. Third, after COVID-19, topics and keywords related to coronavirus showed that the cultural trends were reflected on appreciation, activities, and dailiness based on natural resources. In sum, the interest in green infrastructure in Seoul has increased after COVID-19. Also, the change of green infrastructure represents the increased demand for experience that reflects the need and expectation for nature. Conclusion: The new trend of green Infrastructure in the pandemic era should be considered in the the individual relaxations & activities.

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

• Journal of Korean Home Economics Education Association
• /
• v.31 no.3
• /
• pp.73-90
• /
• 2019

The purpose of this study was to explore the differences in perceptions of male and female students about population problems and to draw up implications for population education. Using text mining, the report about population problem, which had written by students in population education class, were analysed. After extracting key words, semantic networks were visualized. The results were as follows. First, the high frequency words were the same for each gender. Second, key words based on frequency did not differ depending on gender. And the key words extracted by the correlation analysis and bigram were different. That is, in the semantic network of girls' words, the network of "life"-"marriage"-"birth"-"pregnancy" appeared independently, distinguishing it from male students who showed separate objective links to population problems. Therefore, it drew suggestions that male and female students should be viewed as heterogeneous groups with different cognitive structures on population problems and that the content and methods of population education should be approached differently depending on gender.

• Journal of the Korea Convergence Society
• /
• v.12 no.12
• /
• pp.305-313
• /
• 2021

This study collected and analyzed big data from 1995 to 2020, focusing on the keywords "unwed mother", "single mother," and "single mom" to present appropriate government support policy directions according to changes in perspectives on unwed mothers. Big data collection platform Textom was used to collect data from portal search sites Naver and Daum and refine data. The final refined data were word frequency analysis, TF-IDF analysis, an N-gram analysis provided by Textom. In addition, Network analysis and CONCOR analysis were conducted through the UCINET6 program. As a result of the study, similar words appeared in word frequency analysis and TF-IDF analysis, but they differed by year. In the N-gram analysis, there were similarities in word appearance, but there were many differences in frequency and form of words appearing in series. As a result of CONCOR analysis, it was found that different clusters were formed by year. This study confirms the change in the perspective of unwed mothers through big data analysis, suggests the need for unwed mothers policies for various options for independent women, and policies that embrace pregnancy, childbirth, and parenting without discrimination within the new family form.