This is a community to discuss fandom (fanworks and/or fans) from a quantitative/analytical angle.
This community is a place to discuss past and future analyses, methodology for gathering and analyzing data, and anything else related to fandom stats or surveys. You don't need to be a stats whiz or do analyses yourself to participate in this community. Just be interested in discussing these topics!
Example questions that fandom stats might help address:
- Fanworks: Which tags on AO3 are most commonly used? Which tags get the most kudos? How does this differ from what's popular on Fanfiction.net and other platforms? How is it changing over time?
- Fans: What are the demographics of fandom? Does the sexual orientation of fans correlate with the fanworks they like to read/write? Do different ages of fans prefer different types of fanworks? What are fannish motivations for shipping? (e.g., how many fans care whether their ship becomes canon?)
- Fanlore article on Fandom Statistics
- Destinationtoast's fandom stats master list (contains links to other people's analyses -- please feel free to point out if some are missing)
If you're new here, please feel free to leave a note in the comments on this post introducing yourself and sharing a bit about your fandom interests and past fandom analyses (if applicable). You can also ask any questions about the community here.
If you're new here, please feel free to make a new post and say hi! :) Tell us about what you're interested in, or what your background is, or ask questions.
I mostly produce fanworks in the Sherlock fandom, and some of my analyses are specific to that fandom, but I'm quite interested in fandom as a whole -- what's similar and different across many fandoms and many platforms, how fandom trends change over time, etc.
I mostly do aggregate statistics of fanworks -- rather than analyzing individual stories, I like to look at stats for large categories of fanworks. E.g., how many fanworks use the tag "Angst" on AO3, and what's the average number of kudos they receive. That's partly just because scraping the complete metadata for all the stories on an archive is way more work, though. Likewise, surveys are hard to design and run, so I mostly don't do that sort of data collection. I'm interested in learning more about others' methodologies, though -- and getting feedback on my own!