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A Convergence Study for the Academic Systematization of Cartoon-animation (만화영상학의 학문적 체계화를 위한 융합적 연구)

  • Lim, Jae-Hwan
    • Cartoon and Animation Studies
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    • pp.285-320
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    • 2016
  • Cartoons and Animation are convergent arts created with a composite application of language arts described in the form of literary texts and sounds, plastic arts visualized in the form of artistic paintings, and film arts produced in the form of moving pictures. An academic university major in cartoons and animation studies established in late 20th century however, did not satisfactorily meet the needs in academic research and development and the free expression of artistic creation was limited. In order to systematize the major in cartoons and animation studies, an convergent approach to establish and clarify following are in demand : the terms and definitions, the historical developments, the research areas and methods, the major education and related jobs and start-ups. New culture and arts industries including cartoons, animation, moving images, and games contents are not yet listed in the industries listing service jointly provided online by the portal site Naver.com and Hyung-Seol publishing company. Above all, cartoons and animation are inseparably related to each other that even if one uses the term separately and independently, the meaning may not be complete. So a new combined term "Animatoon" can be established for the major in cartoons and animation studies and also used for its degree with concentrations of cartoons, animation, moving images, games, and etc. In the Introduction, a new combined term Animatoon is defined and explained the use of this term as the name of the major and degree in cartoons and animation studies. In the body, first, the Historical Developments classified Animatoon in the ancient times, the medieval times, and the modern times and they are analyzed with the help of esthetics and arts using examples of mural frescos, animal painting, religion cartoons, caricatures, cartoons, satire cartoons, comics, animation, 2 or 3 dimensional webtoons, and K-toons. Second, the Research Areas of Animatoon reviewed the theories, genres, artworks, and artists and the Research Methods of Animatoon presented the curriculum that integrated the courses in humanities, science technologies, culture and arts, and etc. Third, the Major Education considered Animatoon education in children, young adults, students of the major and the Related Jobs and Start-Ups explored various jobs relating to personal creation of artwork and collective production of business-oriented artwork. In the Conclusion, the current challenges of Animatoon considered personalization of the artists, specialization of the contents, diversification of the types, and liberalization of the art creation. And the direction of improvement advocated Animatoon to be an academic field of study, to be an art, to be a culture, and to be an industry. The importance of cartoons and animation along with videos and games rose in the 21st century. In order for cartoons and animation to take a leading role, make efforts in studying Animatoon academically and also in developing Animatoon as good contents in the cultural industries.

Emoticon by Emotions: The Development of an Emoticon Recommendation System Based on Consumer Emotions (Emoticon by Emotions: 소비자 감성 기반 이모티콘 추천 시스템 개발)

  • Kim, Keon-Woo;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.24 no.1
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    • pp.227-252
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    • 2018
  • The evolution of instant communication has mirrored the development of the Internet and messenger applications are among the most representative manifestations of instant communication technologies. In messenger applications, senders use emoticons to supplement the emotions conveyed in the text of their messages. The fact that communication via messenger applications is not face-to-face makes it difficult for senders to communicate their emotions to message recipients. Emoticons have long been used as symbols that indicate the moods of speakers. However, at present, emoticon-use is evolving into a means of conveying the psychological states of consumers who want to express individual characteristics and personality quirks while communicating their emotions to others. The fact that companies like KakaoTalk, Line, Apple, etc. have begun conducting emoticon business and sales of related content are expected to gradually increase testifies to the significance of this phenomenon. Nevertheless, despite the development of emoticons themselves and the growth of the emoticon market, no suitable emoticon recommendation system has yet been developed. Even KakaoTalk, a messenger application that commands more than 90% of domestic market share in South Korea, just grouped in to popularity, most recent, or brief category. This means consumers face the inconvenience of constantly scrolling around to locate the emoticons they want. The creation of an emoticon recommendation system would improve consumer convenience and satisfaction and increase the sales revenue of companies the sell emoticons. To recommend appropriate emoticons, it is necessary to quantify the emotions that the consumer sees and emotions. Such quantification will enable us to analyze the characteristics and emotions felt by consumers who used similar emoticons, which, in turn, will facilitate our emoticon recommendations for consumers. One way to quantify emoticons use is metadata-ization. Metadata-ization is a means of structuring or organizing unstructured and semi-structured data to extract meaning. By structuring unstructured emoticon data through metadata-ization, we can easily classify emoticons based on the emotions consumers want to express. To determine emoticons' precise emotions, we had to consider sub-detail expressions-not only the seven common emotional adjectives but also the metaphorical expressions that appear only in South Korean proved by previous studies related to emotion focusing on the emoticon's characteristics. We therefore collected the sub-detail expressions of emotion based on the "Shape", "Color" and "Adumbration". Moreover, to design a highly accurate recommendation system, we considered both emotion-technical indexes and emoticon-emotional indexes. We then identified 14 features of emoticon-technical indexes and selected 36 emotional adjectives. The 36 emotional adjectives consisted of contrasting adjectives, which we reduced to 18, and we measured the 18 emotional adjectives using 40 emoticon sets randomly selected from the top-ranked emoticons in the KakaoTalk shop. We surveyed 277 consumers in their mid-twenties who had experience purchasing emoticons; we recruited them online and asked them to evaluate five different emoticon sets. After data acquisition, we conducted a factor analysis of emoticon-emotional factors. We extracted four factors that we named "Comic", Softness", "Modernity" and "Transparency". We analyzed both the relationship between indexes and consumer attitude and the relationship between emoticon-technical indexes and emoticon-emotional factors. Through this process, we confirmed that the emoticon-technical indexes did not directly affect consumer attitudes but had a mediating effect on consumer attitudes through emoticon-emotional factors. The results of the analysis revealed the mechanism consumers use to evaluate emoticons; the results also showed that consumers' emoticon-technical indexes affected emoticon-emotional factors and that the emoticon-emotional factors affected consumer satisfaction. We therefore designed the emoticon recommendation system using only four emoticon-emotional factors; we created a recommendation method to calculate the Euclidean distance from each factors' emotion. In an attempt to increase the accuracy of the emoticon recommendation system, we compared the emotional patterns of selected emoticons with the recommended emoticons. The emotional patterns corresponded in principle. We verified the emoticon recommendation system by testing prediction accuracy; the predictions were 81.02% accurate in the first result, 76.64% accurate in the second, and 81.63% accurate in the third. This study developed a methodology that can be used in various fields academically and practically. We expect that the novel emoticon recommendation system we designed will increase emoticon sales for companies who conduct business in this domain and make consumer experiences more convenient. In addition, this study served as an important first step in the development of an intelligent emoticon recommendation system. The emotional factors proposed in this study could be collected in an emotional library that could serve as an emotion index for evaluation when new emoticons are released. Moreover, by combining the accumulated emotional library with company sales data, sales information, and consumer data, companies could develop hybrid recommendation systems that would bolster convenience for consumers and serve as intellectual assets that companies could strategically deploy.