Computational Representations of Character Significance in Novels

TL;DR

This paper introduces a novel six-component structural model of characters in novels, leveraging large language models to analyze character significance and discussion in 19th-century British literature, offering new computational insights.

Contribution

It develops a comprehensive character model based on literary theory and operationalizes it using LLMs, enabling large-scale analysis of character dynamics and gendered discussion.

Findings

Validated the model on major British novels

Revealed insights into character centrality and gender dynamics

Demonstrated the effectiveness of LLMs in literary analysis

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.