• Title/Summary/Keyword: 소설네트워크서비스

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Webdrama Analysis and Recommendation using Text Mining and Opinion Mining Technique of Social Media (소셜미디어 빅데이터의 텍스트 마이닝과 오피니언 마이닝 기법을 활용한 웹드라마 분석과 제안)

  • Oh, Se-Jong;Kim, Kenneth Chi Ho
    • Cartoon and Animation Studies
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    • s.44
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    • pp.285-306
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    • 2016
  • With the increase use of smartphones, users can consume contents such as webtoon, webnovel and TV drama directly provided by the producers. In this Direct-to-Consumer era, webdrama services from the portal websites are increasing rapidly. Webdramas such as , , and can be analyzed in real time using responses such as unique users, likes, and comments. The analyses used in this research were Social Media Big Data Mining Method and Opinion Mining Method. Specific key words from webdrama can be extracted and viewers positive, neutral or negative emotion can be predicted from the words. The analyses of popular webdramas showed that the established K-Pop Idol member appearance and servicing portal site greatly influence the views, traffics, comments, and likes. Also, 'Mobile TV' proved the effectiveness as another platform other than television. Mobile targeted contents and robust business models still to be developed and identified. Overcoming these few tasks, Korea will be proven to be a webdrama content powerhouse.

Automated Story Generation with Image Captions and Recursiva Calls (이미지 캡션 및 재귀호출을 통한 스토리 생성 방법)

  • Isle Jeon;Dongha Jo;Mikyeong Moon
    • Journal of the Institute of Convergence Signal Processing
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    • v.24 no.1
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    • pp.42-50
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    • 2023
  • The development of technology has achieved digital innovation throughout the media industry, including production techniques and editing technologies, and has brought diversity in the form of consumer viewing through the OTT service and streaming era. The convergence of big data and deep learning networks automatically generated text in format such as news articles, novels, and scripts, but there were insufficient studies that reflected the author's intention and generated story with contextually smooth. In this paper, we describe the flow of pictures in the storyboard with image caption generation techniques, and the automatic generation of story-tailored scenarios through language models. Image caption using CNN and Attention Mechanism, we generate sentences describing pictures on the storyboard, and input the generated sentences into the artificial intelligence natural language processing model KoGPT-2 in order to automatically generate scenarios that meet the planning intention. Through this paper, the author's intention and story customized scenarios are created in large quantities to alleviate the pain of content creation, and artificial intelligence participates in the overall process of digital content production to activate media intelligence.