Capturing Differences in Character Representations Between Communities: An Initial Study with Fandom

TL;DR

This study uses computational methods to analyze how online fandom communities reinterpret characters from Harry Potter, revealing significant differences in character emphasis, associations, and gendered traits across communities and fanfiction genres.

Contribution

It introduces a computational approach to compare character representations across online communities, highlighting community-specific reinterpretations and gendered associations in fan narratives.

Findings

Fandom communities emphasize different characters.

Significant gendered association differences in character descriptions.

Fanfiction scores align with qualitative theories of gender and character re-interpretation.

Abstract

Sociolinguistic theories have highlighted how narratives are often retold, co-constructed and reconceptualized in collaborative settings. This working paper focuses on the re-interpretation of characters, an integral part of the narrative story-world, and attempts to study how this may be computationally compared between online communities. Using online fandom - a highly communal phenomenon that has been largely studied qualitatively - as data, computational methods were applied to explore shifts in character representations between two communities and the original text. Specifically, text from the Harry Potter novels, r/HarryPotter subreddit, and fanfiction on Archive of Our Own were analyzed for changes in character mentions, centrality measures from co-occurrence networks, and semantic associations. While fandom elevates secondary characters as found in past work, the two fan communities prioritize different subsets of characters. Word embedding tests reveal starkly different associations of the same characters between communities on the gendered concepts of femininity/masculinity, cruelty, and beauty. Furthermore, fanfiction descriptions of a male character analyzed between romance pairings scored higher for feminine-coded characteristics in male-male romance, matching past qualitative theorizing. The results high-light the potential for computational methods to assist in capturing the re-conceptualization of narrative elements across communities and in supporting qualitative research on fandom.