• 한국의류학회지
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• 제41권6호
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• pp.1060-1070
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• 2017

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.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1998년도 Proceedings of International Workshop on Advanced Image Technology
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• pp.111-115
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• 1998

The Internet today is teemed with not only text data but also other media such as sound, still and moving images in a variety of formats. Unlike text, however, that can be retrieved easily with the help of numerous search engines, there has been few way to access data of other media unless the exact location or the URL is known. Multimedia data in the WWW are contained in or linked via anchors in the hyper-documents. They can most reliably be retrieved by analyzing the binary data content, which is far from being practical yet by the current state of the art. Instead we present another technique of searching based on textual descriptions which are found at or around the multimedia objects. The textual description used in this research includes file name (URL), anchor text and its context, alternative descriptions found in ALT HTML tage. These are actually the clues assumedly relevant to the contents. Although not without a possibility of missing or misinterpreting images and sounds, the description-based search is highly practical in terms of computation. The prototype search engine will soon be deployed to the public service through the prestige search engine, InfoDetective, in Korea.

• 한국의류학회지
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• 제43권3호
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• pp.427-439
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• 2019

This study investigated the semantic network based on the focus of the fashion image and SNS text utilized by global SPA brands on the last seven years in terms of the quantity and quality of data generated by the fast-changing fashion trends and fashion content-based media environment. The research method relocated frequency, density and repetitive key words as well as visualized algorithms using the UCINET 6.347 program and the overall classification of the text related to fashion images on social networks used by global SPA brands. The conclusions of the study are as follows. A common aspect of global SPA brands is that by looking at the basis of text extraction on SNS, exposure through image of products is considered important for sales. The following is a discriminatory aspect of global SPA brands. First, ZARA consistently exposes marketing using a variety of professions and nationalities to SNS. Second, UNIQLO's correlation exposes its collaboration promotion to SNS while steadily exposing basic items. Third, in the case of H&M, some discriminatory results were found with other brands in connectivity with each cluster category that showed remarkably independent results.

• 한국콘텐츠학회논문지
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• 제18권7호
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• pp.282-290
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• 2018

본 연구는 Hobbs의 미디어교육 모형과 Vanhoozer의 미디어텍스트 분석모형에 기초하여 기독교대학 글쓰기 교육모형을 개발하여 제시하고자 하였다. 본 연구가 개발한 모형은 기독교 세계관 수립, 접근, 분석과 평가, 창작, 성찰, 사회적 실천의 6 단계로 구성되어 있으며 기독교대학의 교양과목인 "독서와 글쓰기" 과목에 적합하도록 개발되었다. 개발된 모형은 소리, 이미지, 글자 등의 복합텍스트의 비판적 '수용'을 토대로 대안적 '창작'을 주요 활동으로 하는 미디어텍스트 글쓰기 교육에 적합한 모형으로 기독교대학이 추구하는 교육 목적인 지성, 덕성, 영성이 조화된 인재형을 양성할 수 있도록 구안되었다. 이 모형은 새 시대에 맞도록 학생 친화적이면서도 융합적인 텍스트 쓰기를 지향하고 있으며 대학에서 강조되어야 할 다양한 유형의 문자 글쓰기 역량 역시 제고할 수 있다는 장점이 있다.

• 한국콘텐츠학회논문지
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• 제13권1호
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• pp.164-174
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• 2013

스마트폰의 급속한 보급과 함께 카카오톡, 페이스북, 문자메시지와 같은 문자기반 매체의 활용도가 증가하여 대인간의 주요 의사소통 매체로서 자리 잡고 있다. 본 연구에서는 문자기반 매체들에서 사회적 현존감이 서로 다르게 인지되고 있다는 점에 착안하여 각 매체별로 인지되는 사회적 현존감을 비교 분석하기 위해 설문을 구성하여 데이터를 수집하였다. 분석 결과 사용자는 자신이 가장 많이 사용하는 매체가 사회적 현존감이 높다고 인식하고 있었으며, 매체별로는 카카오톡, 페이스북, 문자메시지 순으로 사회적 현존감이 높게 인식되고 있었고, 각 매체별 사회적 현존감에는 차이가 있는 것으로 나타났다. 사용자가 사회성이 높고, 20대 이하이며, 학생일수록 다른 그룹들보다 사회적 현존감을 상대적으로 높게 인식하는 것으로 나타났다. 사회적 현존감이 실제 사용에 있어 영향을 미치고 있음을 찾아낸 본 연구에 후속으로는 어떠한 매체적 특성이 사회적 현존감의 차이를 불러일으키는지 연구가 필요할 것으로 보인다.

• Journal of Korea Trade
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• 제24권8호
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• pp.39-62
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• 2020

Purpose - Korean exports account for a vast proportion of Korean GDP, and large volumes of Korean products are sold in the United States. Identifying and characterizing actual and potential product hazards related to Korean products is critical to safeguard Korean export trade, as severe quality issues can impair Korea's reputation and reduce global consumer confidence in Korean products. In this study, we develop country-of-origin-based product risk analysis methods for social media with a specific focus on Korean-labeled products, for the purpose of safeguarding Korean export trade. Design/methodology - We employed two social media datasets containing consumer-generated product reviews. Sentiment analysis is a popular text mining technique used to quantify the type and amount of emotion that is expressed in the text. It is a useful tool for gathering customer opinions regarding products. Findings - We document and discuss the specific potential risks found in Korean-labeled products and explain their implications for safeguarding Korean export trade. Finally, we analyze the false positive matches that arise from the established dictionaries that were used for risk discovery and utilize these classification errors to suggest opportunities for the future refinement of the associated automated text analytic methods. Originality/value - Various studies have used online feedback from social media to analyze product defects. However, none of them links their findings to trade promotion and the protection of a specific country's exports. Therefore, it is important to fill this research gap, which could help to safeguard export trade in Korea.

• 전기학회논문지
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• 제57권10호
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• pp.1883-1887
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• 2008

Most of digital media contents are composed with video and audio, picture and animation informations. Sometime, there is some deviation of information recognition quality for the video and audio information according to information receiver's characteristics or the understanding. But visual information using the text provide most clear and accurate ways for information recognition to human being. In this paper, we propose a new broadcasting system(BSDMC) to transmit clear and accurate meaning of the digital media contents. We implement general-purpose components to display the video, picture, text and symbol simultaneously. Only plug-in and call these components with proper parameters on the application developing tool, we can easily develop the multimedia contents broadcasting system. These components are implemented based on the object-oriented framework and modular structure so that increase the reusability and can be develop other applications quick and reliable.

• Journal of Contemporary Eastern Asia
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• 제16권2호
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• pp.59-81
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• 2017

The emergence of the new audiences floating across multimedia platforms and engaging in TV production and distribution have forced producers and broadcasters to think of not only the fragmented distribution of their content but also the development of a new format beyond the frame of traditional TV production. A Korean entertainment TV show My Little Television combining the form of live webcasting and traditional TV show reflects such a trend. Because of the distinct format, My Little Television carries out a unique strategy in managing the two screens - Internet and TV. The dualistic production requires all players to understand not only online subculture and communication styles and methods, but also implicit and explicit rules of traditional TV production. Through text and visual image analysis on the show, this study discusses how MLT negotiates with the original Internet text, the producers' paratext, and the supertext of the national TV network in the context of the transitory screen culture.

• Asia Marketing Journal
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• 제22권3호
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• pp.71-85
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• 2020

Social media has emerged as a major hub of engagement between brands and consumers in recent years, and allows user-generated content to serve as a powerful means of encouraging communication between the sides. However, it is challenging to negotiate user-generated content owing to its lack of structure and the enormous amount generated. This study focuses on the hashtag, a metadata tag that reflects customers' brand perception through social media platforms. Online users share their knowledge and impressions using a wide variety of hashtags. We examine hashtags that co-occur with particular branded hashtags on the social media platform, Instagram, to derive insights about brand perception. We apply text mining technology and network analysis to identify the perceptions of brand images among consumers on the site, where this helps distinguish among the diverse personalities of the brands. This study contributes to highlighting the value of hashtags in constructing brand personality in the context of online marketing.

• International Journal of Advanced Culture Technology
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• 제11권3호
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• pp.332-337
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• 2023

The purpose of the study was to analyze consumers' perceptions of gamification. Based on the analyzed data, we would like to provide data by systematically organizing the concept, game elements, and mechanisms of gamification. Recently, gamification can be easily found around medical care, corporate marketing, and education. This study collected keywords from social media portal sites Naver, Daum, and Google from 2018 to 2023 using TEXTOM, a social media analysis tool. In this study, data were analyzed using text mining, semantic network analysis, and CONCOR analysis methods. Based on the collected data, we looked at the relevance and clusters related to gamification. The clusters were divided into a total of four clusters: 'Awareness of Gamification', 'Gamification Program', 'Future Technology of Gamification', and 'Use of Gamification'. Through social media analysis, we want to investigate and identify consumers' perceptions of gamification use, and check market and consumer perceptions to make up for the shortcomings. Through this, we intend to develop a plan to utilize gamification.