With the rapid development of artificial intelligence technology, AIGC has gradually become one of the most important tools for animation creation, especially in the field of short film animation, showing a wide range of application potential. The purpose of this paper is to collect and analyse data from the comment sections of b-station videos, in order to explore the emotional attitudes of Chinese viewers towards AIGC animated short films and the issues of concern. This study uses natural language processing techniques, combined with sentiment analysis and LDA topic modelling methods, to analyse 8336 valid comments. It is found that the audience’s emotional perception of AIGC animation shows diverse attitudes; the audience highly evaluates the technical innovation and visual effects of AIGC animation, but still has reservations about AIGC animation in terms of plot depth and emotional expression. The comments focus on six aspects: music adaptation and emotional transmission, technical performance and industry performance expectations, AI technology and tools exploration, characterisation and stylised expression, storyline and emotional resonance, philosophical inspiration and cultural reflection. This study can provide reference value for the future development of AIGC animation.

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A Study of Viewers’ Emotional Perceptions of AIGC Animation–An Example of a Review of an Award-Winning Short Film

  • Yuqing Xu,
  • Ruiyuan Peng,
  • Jun Wu

摘要

With the rapid development of artificial intelligence technology, AIGC has gradually become one of the most important tools for animation creation, especially in the field of short film animation, showing a wide range of application potential. The purpose of this paper is to collect and analyse data from the comment sections of b-station videos, in order to explore the emotional attitudes of Chinese viewers towards AIGC animated short films and the issues of concern. This study uses natural language processing techniques, combined with sentiment analysis and LDA topic modelling methods, to analyse 8336 valid comments. It is found that the audience’s emotional perception of AIGC animation shows diverse attitudes; the audience highly evaluates the technical innovation and visual effects of AIGC animation, but still has reservations about AIGC animation in terms of plot depth and emotional expression. The comments focus on six aspects: music adaptation and emotional transmission, technical performance and industry performance expectations, AI technology and tools exploration, characterisation and stylised expression, storyline and emotional resonance, philosophical inspiration and cultural reflection. This study can provide reference value for the future development of AIGC animation.