Archetypes and gender in fiction: A data-driven mapping of gender stereotypes in stories

TL;DR

This paper uses data-driven archetype analysis to explore gender stereotypes in fiction, revealing persistent traditional patterns and nuanced differences in character archetypes across genders.

Contribution

It introduces archetypometrics to quantitatively analyze gendered character archetypes in a large dataset of fictional characters, highlighting societal implications.

Findings

Female characters tend toward Hero, Adventurer, Diva, and Sophisticate archetypes.

Male characters tend toward Fool, Traditionalist, Outcast, Brute archetypes.

Gendered archetype patterns reflect and reinforce societal stereotypes.

Abstract

Fictional character representations reflect social norms and biases. For example, women are relatively underrepresented in television and film, irrespective of genre, and are frequently stereotyped in these media. Here, we draw on a data-driven operationalization of archetypes -- archetypometrics -- to explore the characterization of 2,000 canonically male and female characters. From an overall space of six pairs of base archetypes, we find that canonically female characters tend more toward Hero, Adventurer, Diva, and Sophisticate archetypes, while male characters, tend toward Fool, Traditionalist, Outcast, Brute and Outcast types. However, overarching patterns by gender nevertheless sustain traditional stereotypes: The seemingly positive heroic bias toward females is undercut by heroic female characters being more masculine than other female characters. We discuss the societal implications of skewed archetype representation by character gender.