The research paradigm of post-classical narratology evolves after the AI era

Abstract

The intervention of artificial intelligence technology is driving a profound evolution in the research paradigm of postclassical narratology. This paper examines this theoretical transformation from three dimensions: methodological innovation, the reconstruction of subjectivity, and the expansion of textuality. At the methodological level, the computational turn shifts narrative analysis from interpretive description to computable verification, and quantitative models provide new operational pathways for the study of narrative structure. At the level of subjectivity, generative pre-trained models extend narrative production into the realm of algorithmic systems; the emergence of non-human narrators and the diffusion of authorship compel narratology to reconsider the concept of the subject. At the level of textuality, the digital generation of transmedia narratives breaks the centrality of linguistic signs, and multimodal fusion along with algorithmic curation reshapes the mode of existence of narrative. These transformations do not negate classical narratology; rather, they represent a necessary expansion of its theoretical framework in the AI era, marking a fundamental shift in narratological research from an anthropocentric paradigm to a human-machine symbiotic paradigm.