AΙ Augmented Legend Narratives on Tiktok: When the Acting Parts Become the Tellers of Their Own Stories
Abstract:
In an era when data visualization underpins digital communication, visually driven social platforms—TikTok foremost among them—increasingly integrate generative tools to enrich user expression. Building on this premise, the present study examines how content-creators on TikTok employ AI-generated imagery and narrative scripts to animate contemporary legends, a narrative genre that has been continually renegotiated across successive social-media innovations. Accordingly, drawing on a longitudinal research that combines actor-based and top ic-based methodologies, a purposive sample of AI-augmented legend videos is being analyse alongside their associated user engagements to identify which morphological and functional features are amplified through this practice. The findings reveal that, beyond visually rendering plot elements, AI integration produces a significant narra tive shift: from conventional third-person recounting to first-person testimony, thereby empowering characters— whether villain or victim—to tell their own story. This innovation transforms the genre’s traditional role as a cautionary story into a form of immersive entertainment that provokes fear. Finally, comment-thread analysis illuminates’ patterns of perceived authenticity, collaborative storytelling, and ethical reflection, underscoring the complex dynamics of legend diffusion in AI-mediated environments.
