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소셜미디어 텍스트마이닝을 통한 패션디자인 사용자 인식 조사
안효선,박민정 한국의류학회 2017 한국의류학회지 Vol.41 No.6
This study seeks methods to analyze users' perception in fashion designs shown in social media using textmining analysis methods. The research methods selected ‘men's stripe shirts’ as subjects and collected texts related to the subject mainly from blogs. Texts from 13,648 posts from November 1st, 2015 to October 31st, 2016 were analyzed by applying the LDA algorithm and content analysis. As a result, the wearing status per season and subjects of men's stripe shirts were derived. Across the entire period, the main topics discussed by users to be pattern, customized suits, brands, coordination and purchase information. In terms of seasons, spring time showed the sharing of information on coordinating daily looks or boyfriend looks, and during the winter season the information shared were about shirts suitable for special occasions such as job interviews and stripe shirts that match suits. The study results showed that text-mining analysis is capable of analyzing the context and provide a user-centered index responding to demands newly mentioned by users along with the rapid changes in fashion design trends.
챗봇 기반의 개인화 패션 추천 서비스 향상을 위한 사용자-제품 속성 제안
안효선,김성훈,최예림 한국패션비즈니스학회 2023 패션 비즈니스 Vol.27 No.3
The e-commerce fashion market has experienced a remarkable growth, leading to an overwhelming availability of shared information and numerous choices for users. In light of this, chatbots have emerged as a promising technological solution to enhance personalized services in this context. This study aimed to develop user-product attributes for a chatbot-based personalized fashion recommendation service using big data text mining techniques. To accomplish this, over one million consumer reviews from Coupang, an e-commerce platform, were collected and analyzed using frequency analyses to identify the upper-level attributes of users and products. Attribute terms were then assigned to each user-product attribute, including user body shape (body proportion, BMI), user needs (functional, expressive, aesthetic), user TPO (time, place, occasion), product design elements (fit, color, material, detail), product size (label, measurement), and product care (laundry, maintenance). The classification of user-product attributes was found to be applicable to the knowledge graph of the Conversational Path Reasoning model. A testing environment was established to evaluate the usefulness of attributes based on real e-commerce users and purchased product information. This study is significant in proposing a new research methodology in the field of Fashion Informatics for constructing the knowledge base of a chatbot based on text mining analysis. The proposed research methodology is expected to enhance fashion technology and improve personalized fashion recommendation service and user experience with a chatbot in the e-commerce market.
빅데이터 텍스트 분석을 기반으로 한 패션디자인 평가 연구 -디자인 속성과 감성 어휘의 의미연결망 분석을 중심으로-
안효선,박민정 한국의류학회 2018 한국의류학회지 Vol.42 No.3
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.
유튜브 댓글을 통해 살펴본 버추얼 인플루언서에 대한 인식 연구 -캐릭터 디자인에 대한 긍부정 감성 반응을 중심으로-
안효선,김지영 한국의류학회 2023 한국의류학회지 Vol.47 No.5
This study analyzed users' emotional responses to VI character design through YouTube comments. The researchers applied text-mining to analyze 116,375 comments, focusing on terms related to character design and characteristics of VI. Using the BERT model in sentiment analysis, we classified comments into extremely negative, negative, neutral, positive, or extremely positive sentiments. Next, we conducted a co-occurrence frequency analysis on comments with extremely negative and extremely positive responses to examine the semantic relationships between character design and emotional characteristic terms. We also performed a content analysis of comments about Miquela and Shudu to analyze the perception differences regarding the two character designs. The results indicate that form elements (e.g., voice, face, and skin) and behavioral elements (e.g., speaking, interviewing, and reacting) are vital in eliciting users' emotional responses. Notably, in the negative responses, users focused on the humanization aspect of voice and the authenticity aspect of behavior in speaking, interviewing, and reacting. Furthermore, we found differences in the character design elements and characteristics that users expect based on the VI's field of activity. As a result, this study suggests applications to character design to accommodate these variations.
K 패션에 대한 글로벌 미디어 보도 경향 분석-다이내믹 토픽 모델링(Dynamic Topic Modeling)의 적용-
안효선,김지영 한국의류학회 2022 한국의류학회지 Vol.46 No.6
This study seeks to investigate K-fashion's external image by examining the trends in global media reporting. It applies Dynamic Topic Modeling (DTM), which captures the evolution of topics in a sequentially organized corpus of documents, and consists of text preprocessing, the determination of the number of topics, and a timeseries analysis of the probability distribution of words within topics. The data set comprised 551 online media articles on ‘Korean fashion’ or ‘K-fashion’ published on Google News between 2010 and 2021. The analysis identifies seven topics: ‘brand look and style,’ ‘lifestyle,’ ‘traditional style,’ ‘Seoul Fashion Week (SFW) event,’ ‘model size,’ ‘K-pop,’ and ‘fashion market,’ as well as annual topic proportion trends. It also explores annual word changes within the topic and indicates increasing and decreasing word patterns. In most topics, the probability distribution of the word ‘brand’ is confirmed to be on the increase, while ‘digital,’ ‘platform,’ and ‘virtual’ have been newly created in the ‘SFW event’ topic. Moreover, this study confirms the transition of each K-fashion topic over the past 12 years, along with various factors related to Hallyu content, traditional culture, government support, and digital technology innovation.
패션 크리에이티브 디렉터 변화에 따른 디자인 연관 이슈 비교- 구찌 컬렉션에 대한 소셜미디어 게시글 분석을 중심으로 -
안효선,박민정 한국의류산업학회 2019 한국의류산업학회지 Vol.21 No.3
This study analyzes the online issues of design innovation by a fashion creative director. The study selected fashion house Gucci as the main subject and analyzed social media posts. As for study methods, a social matrix program Textom 2.0 collected 13,014 nouns and adjectives using ‘Gucci Collection’ as a search keyword from Naver Blogs from March to August 2014 and from March to August 2016. Design related issues were derived through semantic network analysis using Ucinet6 and the NetDraw program. The results of the keyword frequency analysis showed that social media user interest for the Gucci collection increased based on the rapid increase in the number of posts from 1,064 to 2,126 after changing the fashion creative director. The results of visualization of semantic network analysis and content analysis also showed that the main issues related to the Gucci collection design changed after the replacement of the fashion creative director. The study found that issues formed around the product information worn by celebrities for promotion purposes during the 2014 period; however, during the 2016 period, issues were formed around ‘vintage' and ‘retro' runway concepts with design styles related to Alessandro Michele, the new creative director.
An AI-based Clothing Design Process Applied to an Industry-university Fashion Design Class
안효선,박민정 한국의류학회 2023 한국의류학회지 Vol.47 No.4
This research aims to develop based clothing design process tailored to the industry-university collaborative setting and apply it in a fashion design class. into three distinct phases: designing and organizing our fashion design class, conducting our class at a university, and gathering student feedback. First, we conducted a literature review on employing new technologies in traditional clothing design processes. We consulted with industry professionals from the Samsung C&T Fashion Group to develop an AI-based clothing design process. We then developed in-class learning activities that leveraged fashion brand product databases, a supervised learning AI model, and operating an AI-based Creativity Support Tool (CST). Next, we setup an industry-university fashion design class at a university in South Korea. Finally, we obtained feedback from undergraduate students who participated in the class. The survey results showed a satisfaction level of 4.7 out of 5. The evaluations confirmed that the instructional methods, communication, faculty, and student interactions within the class were both adequate and appropriate. These research findings highlighted that our AI-based clothing design process applied within the fashion design class led to valuable data-driven convergent thinking and technical experience beyond that of traditional clothing design processes.
발레지도자의 멘토링 역할과 성취목표성향, 발레몰입 및 발레지속의도의 구조적 관계
안효선 한국체육과학회 2022 한국체육과학회지 Vol.31 No.2
This study has a main purpose that closely examines the structural relationships among mentoring role, achievement goal orientation, ballet flow and ballet adherence intention of ballet academy. In order to achieve it, the sample from customer of ballet academy were accumulated by using convenience sampling that chose ballet academy. The samples were 258 people. and we excluded unsuitable sheet like that were decided as untrustful one and an omission and unclear. So the final samples were 236 people. On the basis of that, The statistical techniques, spss 24.0 and amos 24.0 program have been used for the analysis as per research purpose. The statistical analysis used in the research for a data analysis includes frequency analysis, confirmatory factor analysis, reliability analysis, correlation analysis, and structure equation model analysis. The research has drawn the following conclusions, based on the above mentioned research method and its procedures: First, The mentoring role influences achievement goal orientation. Second, The achievement goal orientation quality influences ballet flow. Third, The achievement goal orientation influences ballet adherence intention. Fourth, The ballet flow influences ballet adherence intention.