The Research Paradigm of Post-Classical Narratology Evolves After the AI Era

Abstract

With the advent of artificial intelligence, many changes have occurred in the research model of postclassical narratology. The three directions of the theoretical change in this paper are methodological innovation, reconstruction of subjectivity and expansion of textuality. With the development of computation, narrative analysis has moved from interpretive description to computable verification at the level of methodology, and thus, quantitative models have been introduced to study the structure of narratives. At the level of subjectivity, generative pre-trained models have extended narrative creation to the field of algorithmic systems, and with the appearance of non-human narrators and the spread of authorship, narratology has been forced to reconsider the concept of the subject. At the level of textuality, the new generation of transmedia narratives is no longer made up of linguistic signs; rather, multimodality and algorithmic curation have changed how these stories are told. Although this change is not in conflict with traditional narratology, it is necessary for the development of the theoretical system in the era of artificial intelligence, and thus narratological research has shifted from an anthropocentric view to a human-machine symbiotic one.