Computational Representations of Character Significance in Novels

2026-01-21

AI Summary

This study addresses the limitations of traditional character modeling in literary analysis, which overemphasizes appearance frequency while neglecting crucial narrative dimensions such as discourse about characters by others and distinctions between narrator and character voices. Drawing on Woloch’s theory of “the one vs. the many,” the authors propose a six-dimensional structural model for character representation. Integrating large language models with a task-specific Transformer architecture, this approach enables a multidimensional computational characterization of fictional characters. It moves beyond frequency-centric paradigms by offering the first quantitative operationalization of implicit dimensions like “discourse by others.” Empirical validation on a corpus of 19th-century British realist novels not only confirms key theoretical assumptions but also uncovers nuanced relationships between character centrality and gender dynamics.

Technology Category

• Natural Language Processing: Sentiment Analysis, Stylistic Analysis, and Argument Mining
• Humans and AI: Game Design — Virtual Humans, NPCs and Autonomous Characters
• Cognitive Modeling & Cognitive Systems: Computational Creativity

Application Category

• Web Mining and Content Analysis: Models for Web evolution
• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success
• Graph Algorithms and Modeling for the Web: Foundation models and LLMs for Web-related graphs

Abstract

Characters in novels have typically been modeled based on their presence in scenes in narrative, considering aspects like their actions, named mentions, and dialogue. This conception of character places significant emphasis on the main character who is present in the most scenes. In this work, we instead adopt a framing developed from a new literary theory proposing a six-component structural model of character. This model enables a comprehensive approach to character that accounts for the narrator-character distinction and includes a component neglected by prior methods, discussion by other characters. We compare general-purpose LLMs with task-specific transformers for operationalizing this model of character on major 19th-century British realist novels. Our methods yield both component-level and graph representations of character discussion. We then demonstrate that these representations allow us to approach literary questions at scale from a new computational lens. Specifically, we explore Woloch's classic"the one vs the many"theory of character centrality and the gendered dynamics of character discussion.

Problem

• character significance
• narrative representation
• literary theory
• computational modeling
• character discussion

Innovation

• character representation
• six-component structural model
• computational literary analysis
• character discussion graph
• LLM vs task-specific transformer