Exploring the Formation Mechanism of Hit AIGC Motion Comics: A Case Study of Wan Yao Tu Lu Zhuan
Abstract
With the iterative application of AIGC cross-modal technology, AI motion comics have gradually grown into an emerging category in the vertical-screen digital audiovisual field, yet problems such as homogenization, insufficient user retention, and a low hit rate have become increasingly apparent. Technology can improve content production efficiency, but it cannot directly answer why an AI motion comic can sustain audience attention. On this basis, this paper takes Wan Yao Tu Lu Zhuan as a case and adopts a combination of case analysis, content analysis, and public data analysis to examine the formation process of its hit status from four dimensions: gratification narrative, technological empowerment, platform recommendation, and user dissemination. The study finds that the synergy of high-density gratification narrative, differentiated Chinese-style visual expression, a positive algorithmic traffic cycle, and cross-platform word-of-mouth dissemination constitutes the core driving force behind the work's long-term breakthrough beyond its original audience circle.
References
- The Paper. (2026, July 24). Behind the continuous loss of AI comic drama audiences: Template faces cause "physiological aversion," thousands of dramas with the same formula—who can still immerse themselves and release emotions?36Kr. https://36kr.com/p/3908248131000192
- Yingyi Dushu. (2026, July 16). Hongguo's first comic drama with over 100 million popularity is born: What makes "The Legend of Ten Thousand Demons" stand out?Tencent News. http://news.qq.com/rain/a/20260716A0B9EJ00
- Li, S. D., & Xie, X. Y. (2026). Research on the creation paradigm and industrial governance of AI comic dramas driven by artificial intelligence.China Market, (24), 69–72.
- Zheng, X. J., Liu, R. J., & Li, Y. X. (2025). Disruption and reinvention: AIGC's revolutionary approach to the micro-drama industry.Journal of North University of China (Social Science Edition), 41(4), 57–66.
- Zhou, J. D., & Zhou, Z. X. (2026). Technology iteration and content innovation: Research on the development path of the micro-drama industry.China Radio & TV Academic Journal, 1–5. https://link.cnki.net/urlid/11.1746.G2.20260703.1017.002
- Chen, L. L. (2026). AI generation and film copyright: Ownership, infringement determination, and institutional response.Chinese Film Market, (7), 39–44.
- Toutiao. (2026, July 24). Eighty-five cents for twenty thousand faces: The face collision dilemma of AI comic dramas and the only way out.Toutiao. http://m.toutiao.com/group/7665904565249638950/
- Shi, B., Zhang, H. M., & Xu, P. T. (2025). Research on the creation mode of vertical-screen micro-drama camera language driven by content generation technology.Comparative Study of Cultural Innovation, 9(27), 35–39.
- Daxiong Liao AI. (2026, July 3). What makes "The Legend of Ten Thousand Demons" push AI short dramas to a new height [Video].Douyin. https://www.iesdouyin.com/share/video/7658238724643376427
- Csikszentmihalyi, M. (1990).Flow: The psychology of optimal experience. Harper & Row.
- Zhang, X. L., Zhang, X., & Xu, M. Y. (2025). The manufacturing of instant gratification: How algorithmic narratives in micro-dramas engineer affective trigger efficacy.New Media and Society, (6), 327–343, 489–490.
- Katz, E., Blumler, J. G., & Gurevitch, M. (1973). Uses and gratifications research.Public Opinion Quarterly, 37(4), 509–523.
- Hu, Y. (2026). A multi-dimensional analysis of traffic logic in the digital cultural ecosystem.China Literature and Art Criticism, (2), 4–20, 124.
- Xia, Y. L., & Si, X. X. (2025). Technology empowerment and creative democratization: On the reshaping of AI technology's production affordances for micro-dramas.New Media Research, 11(24), 47–51.
- Gillespie, T. (2014). The relevance of algorithms. In T. Gillespie, P. J. Boczkowski, & K. A. Foot (Eds.),Media technologies: Essays on communication, materiality, and society. MIT Press.