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Perspectives on Fashion Technology during the Pandemic Era - A Mixed Methods Approach Using Text Mining and Content Analysis - (팬데믹 시기의 패션 테크놀로지에 관한 시각 - 텍스트 마이닝과 내용 분석을 중심으로 -)

  • Kim, Mikyung;Yim, Eunhyuk
    • 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.

On the Analysis of Natural Language Processing Morphology for the Specialized Corpus in the Railway Domain

  • Won, Jong Un;Jeon, Hong Kyu;Kim, Min Joong;Kim, Beak Hyun;Kim, Young Min
    • International Journal of Internet, Broadcasting and Communication
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    • v.14 no.4
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    • pp.189-197
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    • 2022
  • Today, we are exposed to various text-based media such as newspapers, Internet articles, and SNS, and the amount of text data we encounter has increased exponentially due to the recent availability of Internet access using mobile devices such as smartphones. Collecting useful information from a lot of text information is called text analysis, and in order to extract information, it is performed using technologies such as Natural Language Processing (NLP) for processing natural language with the recent development of artificial intelligence. For this purpose, a morpheme analyzer based on everyday language has been disclosed and is being used. Pre-learning language models, which can acquire natural language knowledge through unsupervised learning based on large numbers of corpus, are a very common factor in natural language processing recently, but conventional morpheme analysts are limited in their use in specialized fields. In this paper, as a preliminary work to develop a natural language analysis language model specialized in the railway field, the procedure for construction a corpus specialized in the railway field is presented.

Crisis Communication on Social Media during COVID-19 Pandemic: An Analysis of Facebook and YouTube (코로나19 상황에서의 소셜미디어를 활용한 위기 커뮤니케이션: 주요국의 페이스북 및 유튜브 활용 비교)

  • Kim, Sohui;Kim, Dongyeon;Ryu, Min Ho
    • Journal of Korea Society of Industrial Information Systems
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    • v.26 no.6
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    • pp.47-60
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    • 2021
  • Since the outbreak of COVID-19 in 2019, the pandemic has been prolonged. This study compares and analyzes the degree of social media usage, the information type of posts (infectious disease information, promote action, psychological communication), and the level of user engagement in conducting crisis communication by country. We conduct text analysis by collecting information on Facebook and YouTube posts from January 2020 to March 2021 of disease control and prevention agencies in Korea, US, UK, and EU. As a result, the use of social media in Korea and US is higher than of the UK and EU, and all four countries are using social media as a means to provide infectious disease information and to promote action. Although social media can be a means to reach the public psychologically, such as sympathy and respect, there are no posts of psychological communication type on social media in countries other than the US. User engagement with posts is highest in the promotion action type. This study can help define the importance and role of social media in establishing an infectious disease crisis communication strategy.

A Tracking Method of Same Drug Sales Accounts through Similarity Analysis of Instagram Profiles and Posts

  • Eun-Young Park;Jiyeon Kim;Chang-Hoon Kim
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.2
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    • pp.109-118
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    • 2024
  • With the increasing number of social media users worldwide, cases of social media being abused to perpetrate various crimes are increasing. Specifically, drug distribution through social media is emerging as a serious social problem. Using social media channels, the curiosity of teenagers regarding drugs is stimulated through clever marketing. Further, social media easily facilitates drug purchases due to the high accessibility of drug sellers and consumers. Among various social media platforms, we focused on Instagram, which is the most used social media platform by young adults aged 19 to 24 years in South Korea. We collected four types of information, including profile photos, introductions, posts in the form of images, and posts in the form of texts on Instagram; then, we analyzed the similarity among each type of collected information. The profile photos and posts in the form of image were analyzed for similarity based on the SSIM(Structural Simplicity Index Measure), while introductions and posts in the form of text were analyzed for similarity using Jaccard and Cosine similarity techniques. Through the similarity analysis, the similarity among various accounts for each collected information type was measured, and accounts with similarity above the significance level were determined as the same drug sales account. By performing logistic regression analysis on the aforementioned information types, we confirmed that except posts in image form, profile photos, introductions, and posts in the text form were valid information for tracking the same drug sales account.

Senior' Use of Text Messages and SNS and Contact with Informal Social Network Members (노인의 문자메시지 및 SNS 활용역량과 비공식적 사회관계망과의 접촉에 관한 연구)

  • Jung, Chanwoo;Choi, Heejeong
    • Journal of Digital Convergence
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    • v.19 no.3
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    • pp.401-414
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    • 2021
  • The purpose of this study was to examine the associations of Korean older adults' use of Social Network Service (SNS) and text messages with frequency of contact with 1) non-coresident adult children, 2) siblings and relatives, or 3) friends, neighbors, and acquaintances. Data were drawn from the 2017 Survey of Living Conditions and Welfare Needs of Korean Older Persons 65+ (N=8,392), and older adults were categorized into 4 groups depending on their familiarity with use of SNS and text messages. Ordinary Least Squares regression models were estimated for analyses. Results revealed that older users of both types of communication media reported frequent exchanges of calls, text messages, etc. with both family and friends. However, using SNS and text messages was consistently related to more face-to-face contact with non-family members. To conclude, older adults' familiarity with communication media could be key to exchanges of emotional and instrumental support with informal social network members and quality of life in the community. Overall, our results highlight the importance of information communication education targeting older adults for continued involvement with their informal social network members.

Text Mining Driven Content Analysis of Ebola on News Media and Scientific Publications (텍스트 마이닝을 이용한 매체별 에볼라 주제 분석 - 바이오 분야 연구논문과 뉴스 텍스트 데이터를 이용하여 -)

  • An, Juyoung;Ahn, Kyubin;Song, Min
    • Journal of the Korean Society for Library and Information Science
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    • v.50 no.2
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    • pp.289-307
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    • 2016
  • Infectious diseases such as Ebola virus disease become a social issue and draw public attention to be a major topic on news or research. As a result, there have been a lot of studies on infectious diseases using text-mining techniques. However, there is no research on content analysis of two media channels that have distinct characteristics. Accordingly, in this study, we conduct topic analysis between news (representing a social perspective) and academic research paper (representing perspectives of bio-professionals). As text-mining techniques, topic modeling is applied to extract various topics according to the materials, and the word co-occurrence map based on selected bio entities is used to compare the perspectives of the materials specifically. For network analysis, topic map is built by using Gephi. Aforementioned approaches uncovered the difference of topics between two materials and the characteristics of the two materials. In terms of the word co-occurrence map, however, most of entities are shared in both materials. These results indicate that there are differences and commonalties between social and academic materials.

The Image of Ruralism in Korea through a Text Mining for Online News Media analysis (인터넷 뉴스 데이터 텍스트 분석을 통해 본 우리나라 농촌다움에 대한 이미지 연구)

  • Son, Yong-hoon;Kim, Young-jin
    • Journal of Korean Society of Rural Planning
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    • v.25 no.4
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    • pp.13-26
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    • 2019
  • The rural areas in South Korea have changed rapidly in the process of national land development. Rural landscapes have become discoloured, and their attractiveness has decreased as cities have expanded. But the attractiveness or multifunctional values of rural areas has become more important in contemporary society around the world. According to this social demand, the efforts of conserving the rural landscape are of high priority and the recovery of ruralism in the area is required. This study has tried to understand how the public image of ruralism in South Korea has been influenced by the news media. The study retrieved news articles using the web searching portal site from the six keywords, commonly used to refer to ruralism, including 'rural landscape', 'rural community', 'rural tourism', 'rural life', 'rural amenity', and 'rural environment'. News data from the six keywords were also collected respectively from within the year-period of 2004-05, 2007-08, 2012-13, and 2016-17. In the text mining analysis, the nouns with high Degree Centrality were figured out, and the changes by year-period were identified. Then, LDA topic analysis was performed for text datasets of six keywords. As a result, the study found that the news articles gave an informed focus on only a handful of issues such as 'poor rural living condition', 'regional or village improvement projects', 'rural tourism promotion projects', and 'other government support projects'. On the other hand, nouns related to virtues and values in the rural landscape were less shown in news articles. These results have become more apparent in recent years. In the topic analysis, 35 topics were identified. 'village development projects', 'rural tourism', and 'urban-rural exchange projects' were appeared repeatedly in several keywords. Among the topics, there are also topics closely related to ruralism such as 'rural landscape conservation', 'eco-friendly rural areas', 'local amenity resources', 'public interest values of agriculture', and 'rural life and communities'. The study presented an image map showing ruralism in South Korea using a network map between all topics and keywords. At the end of the study, implications for Korean rural area policy and research directions were discussed.

Keyword Analysis of Research on Consumption of Children and Adolescents Using Text Mining (텍스트마이닝을 활용한 아동, 청소년 대상 소비관련 연구 키워드 분석)

  • Jin, Hyun-Jeong
    • Journal of Korean Home Economics Education Association
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    • v.33 no.4
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    • pp.1-13
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    • 2021
  • The purpose of this study is to identify trends and potential themes of research on consumption of children and adolescents for 20 years by analyzing keywords. The keywords of 869 studies on consumption of children and adolescents published in journals listed in Korean Citation Index were analyzed using text mining techniques. The most frequent keywords were found in the order of youth, youth consumers, consumer education, conspicuous consumption, consumption behavior, and character. As a result of analyzing the frequency of keywords by dividing into five-year periods, it was confirmed that the frequency of consumer education was significantly higher betwn 2006 and 2010. Research on ethical consumption has been active since 2011, and research has been conducted on various topics instead of without a prominent keyword during the most recent 5-year period. Looking at the keywords based on the TF-IDF, the keywords related to the environment and the Internet were the main keywords between 2001 and 2005. From 2006 to 2010, the TF-IDF values of media use, advertisement education, and Internet items were high. From 2011 to 2015, fair trade, green growth, green consumption, North Korean defector youths, social media, and from 2016 to 2020, text mining, sustainable development education, maker education, and the 2015 revised curriculum appeared as important themes. As a result of topic modeling, eight topics were derived: consumer education, mass media/peer culture, rational consumption, Hallyu/cultural industry, consumer competency, economic education, teaching and learning method, and eco-friendly/ethical consumption. As a result of network analysis, it was found that conspicuous consumption and consumer education are important topics in consumption research of children and adolescents.

A Study on the Reading Efficiency of Comics (만화의 독서 효용성에 관한 연구)

  • Ryu, Ban-Dee
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.22 no.2
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    • pp.123-139
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    • 2011
  • This study focuses on how the characteristics of the comics make the medium a useful reading material. To highlight how the characteristics of comics enhance the media's capacity for reading, this study analyzed several patterns of adaptation from a comic to other media. The usefulness of comics as a reading text can be summarized as follows: First, comics have alternate phases of immersion and concentration. Second, comics provide the whole view as well as speed. These two factors make the comics as an interesting reading material.

A Methodology for Analyzing Public Opinion about Science and Technology Issues Using Text Analysis (텍스트 분석을 활용한 과학기술이슈 여론 분석 방법론)

  • Kim, Dasom;Wong, William Xiu Shun;Lim, Myungsu;Liu, Chen;Kim, Namgyu;Park, Junhyung;Kil, Wooyeong;Yoon, Hansool
    • Journal of Information Technology Services
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    • v.14 no.3
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    • pp.33-48
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    • 2015
  • Recently, many users frequently share their opinions on diverse issues using various social media. Therefore, many governments have attempted to establish or improve national policies according to the public opinions captured from the various social media. In this paper, we indicate several limitations of traditional approaches for analyzing public opinions about science and technology and provide an alternative methodology to overcome the limitations. First of all, we distinguish science and technology analysis phase and social issue analysis phase to reflect the fact that public opinion can be formed only when a certain science and technology is applied to a specific social issue. Next, we apply a start list and a stop list successively to acquire clarified and interesting results. Finally, to identify most appropriate documents fitting to a given subject, we develop a new concept of logical filter that consists of not only mere keywords but also a logical relationship among keywords. This study then analyzes the possibilities for the practical use of the proposed methodology thorough its application to discovering core issues and public opinions from 1,700,886 documents comprising SNS, blog, news, and discussion.