• Title/Summary/Keyword: Character Web-dramas

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Development of Story Recommendation through Character Web Drama Cliché Analysis (캐릭터 웹드라마 클리셰 분석을 통한 스토리 추천 개발)

  • Hyun-Su Lee;Jung-Yi Kim
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.4
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    • pp.17-22
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    • 2023
  • This study analyzed the genres of popular character web dramas and studied the development of story recommendations through the language model GPT. As a result of the study, it was confirmed that similar cliches are repeated in web dramas. In this study, a common story structure (cliché) was analyzed and a typical story structure was standardized and presented so that even unskilled video producers can easily produce character web dramas. For analysis, clichés of web dramas in the school romance genre, which is the most popular genre among teenagers, were listed in order of success. In addition, this study studied the story recommendation mechanism for users by learning the clichés that were analyzed and cataloged in GPT. Through this study, it is expected to accelerate the production of various contents as well as popular popularity through the acceptance of various databases from the standpoint of database consumption theory of web contents.

Recommendation System Development of Indirect Advertising Product through Summary Analysis of Character Web Drama (캐릭터 웹드라마 요약 분석을 통한 간접광고 제품 추천 시스템 개발)

  • Hyun-Soo Lee;Jung-Yi Kim
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.6
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    • pp.15-20
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    • 2023
  • This paper is a study on the development of an artificial intelligence (AI) system algorithm that recommends indirect advertising products suitable for character web dramas. The goal of this study is to increase viewers' content immersion and help them understand the story of the drama more deeply by recommending indirect advertising products that are suitable for writing lines for web dramas. In this study, we analyze dialogue and plot using the natural language processing model GPT, and develop two types of indirect advertising product recommendation systems, including prop type and background type, based on the analysis results. Through this, products that fit the story of the web drama are appropriately placed, allowing indirect advertisements to be exposed naturally, thereby increasing viewer immersion and enhancing the effectiveness of product promotion. There are limitations of artificial intelligence models, such as the difficulty in fully understanding hidden meanings or cultural nuances, and the difficulty in securing sufficient data for learning. However, this study will provide new insights into how AI can contribute to the production of creative works, and will be an important stepping stone to expand the possibilities of using natural language processing models in the creative industry.