Revisiting Northrop Frye's Four Myths Theory with Large Language Models

2026-02-17

AI Summary

This study addresses a critical gap in computational narratology by systematically examining how character functions vary across Frye’s four mythoi—comedy, romance, tragedy, and satire—a dimension largely overlooked in prior work focused primarily on narrative patterns. Integrating Jungian archetypal theory with Frye’s generic framework, the paper proposes a computable model comprising four universal character functions and their sixteen genre-specific instantiations. The model is rigorously evaluated using six state-of-the-art large language models, employing balanced accuracy and Fleiss’ κ inter-rater reliability on carefully constructed positive–negative sample pairs. Results demonstrate an average balanced accuracy of 82.5% (κ = 0.600), confirming that character functions exhibit structured, genre-dependent variation. Notably, the analysis reveals systematic role distributions in romance and deliberate subversions of archetypes in satire, underscoring the model’s capacity to capture nuanced narrative dynamics across genres.

Technology Category

• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Natural Language Processing: Sentiment Analysis, Stylistic Analysis, and Argument Mining
• Application Domains: Humanities & Computational Social Science

Application Category

• Web Mining and Content Analysis: Models for Web evolution
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

Northrop Frye's theory of four fundamental narrative genres (comedy, romance, tragedy, satire) has profoundly influenced literary criticism, yet computational approaches to his framework have focused primarily on narrative patterns rather than character functions. In this paper, we present a new character function framework that complements pattern-based analysis by examining how archetypal roles manifest differently across Frye's genres. Drawing on Jungian archetype theory, we derive four universal character functions (protagonist, mentor, antagonist, companion) by mapping them to Jung's psychic structure components. These functions are then specialized into sixteen genre-specific roles based on prototypical works. To validate this framework, we conducted a multi-model study using six state-of-the-art Large Language Models (LLMs) to evaluate character-role correspondences across 40 narrative works. The validation employed both positive samples (160 valid correspondences) and negative samples (30 invalid correspondences) to evaluate whether models both recognize valid correspondences and reject invalid ones. LLMs achieved substantial performance (mean balanced accuracy of 82.5%) with strong inter-model agreement (Fleiss' $κ$ = 0.600), demonstrating that the proposed correspondences capture systematic structural patterns. Performance varied by genre (ranging from 72.7% to 89.9%) and role (52.5% to 99.2%), with qualitative analysis revealing that variations reflect genuine narrative properties, including functional distribution in romance and deliberate archetypal subversion in satire. This character-based approach demonstrates the potential of LLM-supported methods for computational narratology and provides a foundation for future development of narrative generation methods and interactive storytelling applications.

Problem

• Northrop Frye
• character function
• narrative genres
• archetypal roles
• computational narratology

Innovation

• character function
• computational narratology
• Large Language Models
• archetypal roles
• genre-specific roles