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Common thread in all of this: it's the cool people and cool stuff they post which makes Mastodon sticky. Not celebs, but people with common interests that post a high density of amazing stuff.
I came to Mastodon as a very experienced social media user and started following breadcrumb trails from hashtags and the local timeline, and quickly found lots of cool people to follow. Most users (even tech savvy ones) seem not motivated enough to do this. (cont)
I'm thinking as I type here, and as an aside (and without having kept abreast of developments), I really wish the best to the forking folks, because I suspect there's a bit of a schism in the community: a big chunk of folks like, use, and want high discoverability, and a big chunk of folks absolutely do not want it, and I suspect in the long run this may need to be solved either by a fork or by configurable features. With that out of the way... (cont)
(cont) I don't agree with the seemingly reactionary stance against nearly every discoverability feature idea that's tossed around, nor do I agree that algorithms are never useful in this context and that all discovery must be 100.0% organic. IMO that's just not realistic. Mastodon is a firehose, and people have limited time.
What about a happy medium with unobtrusive algorithmic onboarding & suggestions which tail off over time as a new user's engagement grows? (cont)
I go back to the "cool people with similar interests" sticky factor. How can we make finding those people easy for noobs?
Principle: can we get the user to specify some interests during onboarding, then make it more likely that content from users with similar interests will be displayed to them at first? (cont)
Idea: aggregate the most general, longest-lived hashtags above a certain usage cutoff, present them to the noob in a "do any of these interest you?" onboarding multiselect. Then:
* during onboarding, suggest one of the more active users in some of the selected hashtags as people for the noob to follow
* until the noob crosses some non-noob threshold, occasionally put recent toots with the selected hashtags into their timeline
To be clear, I'm suggesting an algo that would surface hashtags like "linux" and "cats" and "photography" to present to the user, not "kde" and "blepvideos" and "nikon" - the key would be very broad interest hashtags.
The "algo" here could also be another human-curated list, it'd just need to be well tuned to be broad, and probably based on a study of hashtag use on the fediverse, and updated from time to time.
I think this use of hashtags for onboarding removes most of the harassment concerns raised in prior hashtag feature arguments, particularly if the "don't index my toots" button in privacy settings also opts those users out of being promoted to noobs here.
Further, especially with a little algorithmic randomness, it lacks the thundering herd / concentrating eyeballs problems.
And, it promotes the use of hashtags. If we're not to have full-text search, that's good 