인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Artificially Generated Content (AIGC) is profoundly influencing the film and animation industry. With the rapid advancement of AI technology, China"s practice in AIGC animation has entered a boom phase. "Poems of Timeless Acclaim," the first Chinese AIGC animated short film, was broadcast in 2024, serving as a vivid epitome of AIGC empowering the cultural and creative industries. However, how AIGC animated short films continue to attract audiences remains an area for in-depth exploration. This study, taking the audience of “Poems of Timeless Acclaim” as a case, systematically examines the impact of three-dimensional digital affordances-physical, informational, and interactive-on audiences" continuous watching intentions, with flow experience as a mediating variable. It was found that informational and interactive affordances significantly enhance continuous watching intentions through a positive impact on flow experience, while the influence of physical affordance is relatively limited. This indicates that in the context of AIGC animation, optimizing content information quality and interactivity is crucial. As user habits evolve, the importance of physical device attributes may diminish. This research expands the application of digital affordance theory in the field of AIGC animation, providing theoretical insights into the consumption trends of AIGC-driven audiovisual content, and offering practical guidance for the industry to optimize animation design and enhance user engagement. Future construction of AIGC content ecosystems requires coordinated efforts in content creation, platform operation, and marketing promotion, focusing on enhancing information quality, innovating interaction modes, building immersive experiences, and exploring cultural and emotional values, to promote the healthy development of the AIGC industry with smart, personalized experiences.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
최근 본 자료 전체보기
UCI(KEPA) : I410-151-25-02-090886042