I was playing around with Lemmy statistics the other day, and I decided to take the number of comments per post. Essentially a measure of engagement – the higher the number the more engaging the post is. Or in other words how many people were pissed off enough to comment, or had something they felt like sharing. The average for every single Lemmy instance was 8.208262964 comments per post.
So I modeled that with a Poisson distribution, and I learnt that to a 5% significance level, if your post got less than 4 comments, that was statistically significant. Or in other words – there is a 95% probability that something else caused it not to get more comments. Now that could be because it is an AMAZING post – it covered all the points and no one has anything left to say. Or it’s because it’s a crappy post and you should be ashamed in yourself. Similarly a “good post”, one that gets lots of comments, would be any post that gets more than 13 comments. Anything in-between 4 and 13 is just an average post.
To give you an idea of a more sweeping internet trend, the adage 1% 9% 90%, where 1% do the posting, 9% do the commenting, and 90% are lurkers – assuming each person does an average of 1 thing a day, suggests that c/p should be about 9 for all sites regardless of size.
Now what is more interesting is that comments per post varies by instance, lemmy.world for example has an engagement of 9.5 c/p and lemmy.ml has 4.8 c/p, this means that a “good post” on .ml is a post that gets 9 comments, whilst a “good post” on .world has to get 15 comments. On hexbear.net, you need 20 comments, to be a “good post”. I got the numbers for instance level comments and posts from here
This is a little bit silly, since a “good post”, by this metric, is really just a post that baits lots and lots of engagement, specifically in the form of comments – so if you are reading this you should comment, otherwise you are an awful person. No matter how meaningless the comment.
Anyway I thought that was cool.
Ah nice, I encountered a Poisson-distribution in the wild today. I shall recount this encounter to my children.
Goodhart’s Law: “When a measure becomes a target, it ceases to be a good measure.”
Not entirely sure how this applies to the discussion, it just came to mind lol
I disagree that commenting for the sake of commenting is a good idea. Quality over quantity, a single meaningful discussion is superior to a sea of low effort garbage. I also want the fediverse to take off, but not at the cost of adopting modern Reddit culture.
a “good post”, by this metric, is really just a post that baits lots and lots of engagement
Baiting anything is bad.
Well exactly, that was kind of the point of this post. Hence “good post” being in air quotes. It being a silly idea as well.
Completely agree with you on that last point.
Add a TLDR or this post won’t get a lot of traction either
Confirmed. I see “Poisson distribution” I start skimming lol
This comment will be sad if you don’t engage with it.
This comment is part of a tree-datastructure that represents the branches of discussion.
Ohhh poor thing here have an upvote and a comment.
The comment is very happy to be a good comment with 8 updoots and two replies.
10/9.5 🥳
I comment very seldom and only if i think that I can contribute. I see no need to write anything if I got nothing of significance to add.
Maybe I should. Add comments that is uplifting and kind more often.
I comment a shit ton and often with absolute banalities. Especially on posts with 0 comments.
My reasoning is twofold: first of all I want to encourage posters by engaging with their content so they don’t stop posting. Second I want to invite others to comment and it’s much more inviting to do so if a post has at least one comment. People tend to think it’s dead otherwise and not bother.
I think at the current level of MAUs there is no comment too small, and every little bit helps just by virtue of breaking the silence.
Well said
My meagre contributions pale in comparison to your efforts, but I do what I can.
I feel guilty now. Yes, everything you just said is true.
I shall become a better… Lemming(?) and comment a few times every day.
Interesting numbers, it would be great to see how the statistics look for different “categories” of communities. Interaction based communities (c/ask X) and political communities will naturally garner more comments than information communities. E.g. while you may enjoy the content of blogs posted on !godot@programming.dev or !programming@programming.dev, you’re probably less likely to comment than on !asklemmy@lemmy.world or !casualconversation@lemmy.world
I actually plotted the top 50 or so instances, with user size against comments/post. One of the many outlier instances was lemmynsfw.com which obviously lacks all that much engagement, with a score of around 1 c/p. Which makes quite a bit of sense when you think about it.
I follow instructions, I think. Good post
A post by fediversechick
Average Fediverse Experience:
Post comment
Waits 24 hours
zero replies
zero votes
not even a downvote
check post viewed from other instances
can’t find the comment
realizes that the comment never federated
now too much time has passed since the original time of the post, and the joke you commented is no longer funny anymore
😭
Or other people created the same joke without ever seeing your post
I think one needs to include parameters like how soon after the topic was created the comment was made and how deep is it in the comment tree. If you for instance consistently comment on 1 month old topics or reply on comments ten levels deep you will get very few interactions.
Write a few comments, go to sleep and see for yourself what happens when you wake up. This is how I do it.
Any details you could share about how you obtained and processed the data? It seems like there’s a lot of interesting things that could be done with this but I’m not sure where the best place to start would be
You need a factor for niche communities. A post with 4 comments in a backpacking community with 20 subscribers is way “gooder” than 40 comments in a 5k subscriber news community.
I.E. add a community size factor.
I think the community matters a lot more than the instance. Hexbear has a bunch of coping bubble communities but they keep posting the same low-quality comments, so that’s probably why the threshold of 20 comments is so high. Another example, I make posts to my own blog community !dginovker_blog@lemmy.ml, but there’s no subscribers so there’s never gonna be any comments.
Basically I’m saying you should do this same analysis across a sample of random communities ^^
