Hey! Those are good questions. I don’t know of a ton of relevant data, but I’ll throw it out to my readers – does anyone else know of relevant studies/data?

I do have this comment data I collected recently:

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We can see that nearly three quarters of fanworks on AO3 have fewer than 10 comments. I’ve looked at popularity metrics a number of times in the past, and when I examine the data from this post in 2014, I see that 12 years ago, over 40% of AO3 works had 0 comments (vs. 25% now). And at that time, only 5% of works had 25+ comments, whereas now 6% of works have 50+ comments.

So it looks like maybe things have actually gotten better, right? And possibly they have, in spite of the general sense from authors/creators that they’re getting less feedback than they used to. But OTOH, the older works have now been around longer and had time to accumulate a bunch more comments. This histogram can’t tell us about the age of the works with more comments, nor how quickly the comments have accumulated.

You are also right that fannish attention is probably spread thinner than before. There are a huge number of fandoms on AO3 (76K as of June 2026), and most of those fandoms are very small, meaning that a lot of attention is spread around – and most people in those fandoms are probably not getting nearly as much feedback as people in some of the really big/really active fandoms. (Though I will note as someone who has made the first/only work in a fandom that the people who DO comment on such a work are often extremely enthusiastic to have found it! :) )

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(Sidenote: It’s worth me & other fandom data enthusiasts noting how few fandoms have 10K+ works, given how many fandom stats are about the big fandoms!)

I don’t have historical numbers on fandom sizes for comparison. But I expect that there has been a significant shift toward more smaller fandoms on AO3 (and elsewhere), given how the general cultural attention to media has fragmented over time. I have seen indirect evidence of such fragmentation… I recently compared the popular ships from 2013 to those now (forthcoming work!) and shockingly, most of the top 5 ships are the same now as in 2013. Which is undoubtedly due to a variety of factors, but it is consistent with the idea that fannish attention has spread out from the early mega-fandoms to a much wider set of new fandoms and ships now, and so very few new ships have gotten as much attention as the early mega-ships.

I do think commenting culture has almost certainly changed some over time, too. But it’s a bit tricky figure out how to quantify shifts. Even if we looked at a bunch of random works over AO3 ’s history and compared their numbers of comments to see how average comment number is changing over time, there are complications. As I mentioned before, newer works haven’t had as much time to accumulate comments as older ones. And I’ve also seen in the past that average numbers of kudos/comments/etc. can vary wildly by fandom/ship/tags. But that said, I could imagine sampling a whole bunch of works from different time periods and looking at how quickly they got their first comment, second comment, etc. If commenting has slowed down, then the time to the Nth comment would be longer now than before. (That would only partially address your questions, but could be interesting.) I kinda expect that maybe that’s not true for the new hotness like Heated Rivalry but is true for smaller fandoms, but that’s pure speculation!

I guess I could also write code to scrape my own AO3 inbox info (and my own Works posted dates) to gather the timing info for all the comments on my works. Then I could look at how commenting rate has changed over time for me and my own stories. But that wouldn’t tell me much unless I also got a ton of other people to use my code to scrape their own comment/work timing info and then shared that with me. On the one hand, that could help us look at longitudinal changes on the same creators over time, which would be interesting. On the other hand, it would introduce sampling bias (which creators are sharing their data? probably not a representative set!) and also be a heck of a lot of work. :)

I’m curious whether anyone else has ideas for methods of investigating! Maybe there are survey questions that would also be useful to ask, or other ways to investigate. I think the questions around how much writers overlap with commenters (or anything else involving individual commenter identities), are ones I would hesitate to try to address through scraping due to potential privacy issues – so something like survey questions might be a better approach there.

(Note also that I’m not signing up to do further research here, mind you, but it’s interesting to at least think through what would provide answers to these questions. :) )

One final note: For any histogram of things like number of comments or sizes of fandoms, it’s almost always the case that most things are in the smallest bucket due to power laws. But interestingly, that’s not what we see with comments when we zoom in:

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It’s very cool to see that there are more works with two comments than one, more with four than three, and so on. I think this speaks to how much authors appreciate comments: they often reply, and so comments frequently occur in pairs!

hi! research question I'd love your input on:

do you know how to generate size-of-fandom stats? I'm researching the Ghost fandom and while I know from the This Week in Tumblr posts about what their size is *now,* I'd like to try to compare it to past years, and be able to make statements like "x% of the fandom is reblogging explicit content."

I'm also looking for deeper info on how tumblr works if someone deactivates - do their notes vanish too?

It sounds like you want to gather Tumblr information only – is that right? I don’t have a lot of expertise with Tumblr data (I think I last gathered some over a decade ago), but it looks like their API still lets you retrieve posts with a certain tag and specify a timestamp, if you’re willing to do a bit of programming. So you could, e.g., retrieve the last N posts of each month that use a particular fandom tag. And then you can compare those samples of posts to see how the content has changed over time. If you want to do that, there are libraries in Python and probably other languages that can make it easier to work with the Tumblr API.

I believe the posts retrieved this way don’t include reblogs, so you’d also have to look at the post notes to get info about how many reblogs different types of posts are getting. As to your question of deactivated accounts within those notes, I’m not certain of the answer. I frequently see reblog chains where some accounts in the chain have deactivated, so those notes are not entirely gone. But I don’t know if the replies/likes from deactivated accounts disappear from post notes. Anyone else know?

Good question (and thank you :) )! I just took a look, and I was interested to find that AO3 fanworks have, on average, gotten longer over the past 10 years.

Here’s the data from 2014:

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And here’s updated data from 2024:

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These graphs, along with the data and any clarifications and corrections are also available on AO3.