Media Aesthetics and Communication Effectiveness of Immersive Animated Narrative in Broadcast Television Driven by Generative Artificial Intelligence (GAI)
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Abstract
There are fundamental issues in broadcast TV immersive animated narrative: low usage of technology, low involvement of the audience, and weak aesthetic effect. By applying a hybrid research approach with Generative Artificial Intelligence (GAI) technology, this study develops a three-dimensional perception-cognition-emotion media aesthetic analysis framework for the production of “Narrative Innovation Paths” of “perception-cognition-emotion”. Demand data were gathered from 32 creators and 156 audience members through in-depth interviews, and grounded theory approach was used to extract the encoding of aesthetic elements. Second, it develops a GAI collaborative creation model including visual style transfer, dynamic scene generation and interactive scene branches, and carries out an 8-month experimental deployment in 6 broadcasting stations. Lastly, it employed eye-tracking technology and neuroimaging techniques to measure immersive experience factors. The results showed that the average immersion time of users in the experimental group was 49.0 minutes, an increase of 36.9% compared with the control group; the peak emotional arousal intensity increased by 2.78 times; and the final conversion rate effect size in the content sharing willingness test reached 23.15. This study verifies the significant value of GAI technology in reconstructing narrative space-time, enhancing aesthetic immersion, and optimizing communication effectiveness, providing theoretical support and practical guidance for the transformation of broadcast and television media.
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