College of Humanities
34 Learning About Fan-Fiction Genres via Data Science
Tianye Dai; Anne Jamison; Kate Issacs; and Marina Kogan
Faculty Mentor: Anne Jamison (English, University of Utah)
Abstract
Determining how to categorize works of fiction into genres often leads to debates. Traditionally, when discussing genres, we think of categories such as Fantasy, Mystery, Romance, etc. This research explores genres within fan fiction by analyzing tags that describe the type of content in stories through a data science approach. We construct a network of popular generic tags from Archive of Our Own (AO3), a platform for sharing and reading fan fiction. Using community detection methods, we identify clusters of tags that frequently co-occur in the same story. Additionally, we build another network to examine the connections between these tag clusters. Exploring tags is a potential way of understanding how genres are organized in the fan-fiction community, which tends to be more complex and nuanced compared to traditional genres. This technology-driven method may reveal new genre forms distinct from conventional categories. Our findings provide insights into genre dynamics within this female/LGBTQIA+ centered community, uncovering patterns that warrant further exploration. These insights could be valuable for future researchers seeking to better understand fanf iction community behaviors.
Introduction
In this research, we examine genres in fan fiction through a data science approach. Previously, researchers on fan fiction have often focused on qualitative and literature-focused aspects of the subject. We aim to look at fan fiction from a newer perspective and on a larger scale, using a more quantitative method. We hope our findings will provide other fan-fiction researchers who employ qualitative methods some inspiration on what to focus on in the future.
Fan fiction is a type of story that features characters, settings, or plotlines from existing books, movies, TV shows, or other media. Archive of Our Own (AO3) is a non-profit website where fan-fiction lovers share and read fan fiction, and this is where our data comes from.
When speaking of genres, we typically think of very general terms such as Mystery, Fantasy, Romance, etc. It seems that genre may work in a very different way in fan fiction. People tag their stories to indicate the content and themes of their work, and these tags are much more specific and complex than the traditional genres we know. We’re exploring the relationship between tags by establishing a network to see which tags are closely linked together and the connections between tag groupings. Our findings provide insights into genre dynamics within this female/LGBTQIA+ centered community, uncovering patterns that warrant further exploration and may offer a new way of grouping artistic works into genres.
Methodology
We plan to create a network of the tags using NetworkX, conduct community detection analysis to find clusters of tags