Fan Studies Research Goals and Interests

For my work in fan studies, I am interested in a) ethical research methodologies when working with fans and fan materials (and more generally digital writing research); b) prioritizing role of queer communities, marginalized genders, people of color, and neurally diverse writers and characters in these communities; c) incorporating computational methods to analyze larger corpora of fan texts; d) using Rhetorical Genre Studies to analyze fan uptakes, genres and the embedded ideologies; and d) navigating my positionality as both an active fan and academic.

Digital Writing Research and Positionality

By using digital writing research as a methdological framework, I want to tringulate multiple sources of data, including conversations with other fans, my own experiences, and fan materials to describe genres and ideologies in online fan communities as well as the impact of these literacy practices impact fans relationships with writing and reading.

Computational Methods: Preliminary Findings

With the permission of the Organization for Transformative Works, I used Jingyi Li and Sarah Sterman's Python code to scrape over 7,000 The Legend of Korra fan fiction texts and their metadata from Archive of our Own. I am using Python to conduct computational text analyses on this corpus. Part of my hope for doing computational text analysis is to celebrate the labors of love performed in fan communities; these labors of love often revolve around and are performed by marginalized people, particular women, people from the queer community, and people of color. I also want to think about the relationship between the original text (The Legend of Korra) and fan genres/uptake.

Using this corpus, I have created three different topic models:

I chose these particular models because of the average word counts for each. The average word count for "General Audience" fan fictions is 2,000, while the average word count for "Mature" fan fictions is 20,000. Based on my participation in writing and reading fan fictions for 15 years, I speculates this difference is because "Mature" fan fictions typically build tension between characters to lead to moments of intimacy, while "General Audience" fan fictions are often one-shots, or one chapter that explores a particular moment/idea from the canonical text. Creating these topic models provides a more general understanding, pointing out trends across the corpus. For example, several topics focus around the body, touch, intimacy, and physicality. The concrete descriptions of intimacy suggest a larger genre convention in fanfiction.

As my work continues, I plan to conduct interviews with fanfiction writers and, based on these interviews, I will continue doing computational methods to get a better understanding of the individual fan's experience as compared with larger patterns in a particular corpus that resonates with that fan's experience. For example, if I speak with someone who writes Supernatural fanfic, I may conduct computational text analysis on a Supernatural fanfic corpus to see larger patterns across the board and compare those with that fan's experience.