You're on the "recommended follows" list from Primal, that they use when onboarding new nostr:npubs (which aren't necessarily humans). If there are a lot of people onboarding, but not staying or mostly lurking, you end up with a sky-high follower list, but only marginally-higher interactions than someone unrecommended, like me.

What you have is visibility. Only the "regulars" can usually see my stuff and it can take newbies weeks or months, to stumble upon one of my notes.

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it's an awful onboarding flow

what they should be doing is something more like, show you global, and prompt you to follow ones you like, and then build out recommendations after that

hm

i'm literally working on a recommendation engine right now, and i know the data system very well, have also written a nostr spider for gathering this kind of info

a kind 1 client with a really good onboarding flow would dominate pretty fast i think, because it retains users

i wish i could persuade my boss to start a project like this, it's just, i don't think the people he fundseeks from would be interested

Invites to Communities / Groups will dominate.

And the mEtRiCs might not even notice :winkwithtongue:

i still think that this recommendation engine idea i have will be a killer feature for nostr user retention though... and it can be a service that apps call in the first week or so to get recommendations to populate a recommendation list that discreetly is available to users to click and open

i get it why my boss thinks this is a proper value add for social networks, when i think through my own onboarding experience

it's really not hard to build this out either, although it needs a hefty database that spiders the network and filters it for a compact representation of the data (replies, reposts, quotes, follows, mutes)

well, the idea is in the air, anyway

nostr:npub1syjmjy0dp62dhccq3g97fr87tngvpvzey08llyt6ul58m2zqpzps9wf6wl has been implementing my idea of a service that does reverse proxy for you to expose your personal relay to the network, enabling full decentralized outbox, maybe someone else will build this...

we really need some competent front end devs in this team

Hmm. Best one I know is @Nusa. 🤔

Nusa, do you think a recommendation engine like that would be useful for publications? Like, click your ten favorite publications and we suggest ten more? That sort of thing?

of course nerds are always great recommenders lol, especially the collector type

ohhh nostr:npub1636uujeewag8zv8593lcvdrwlymgqre6uax4anuq3y5qehqey05sl8qpl4 is a front end dev? hmmmm i could think of a few small tasks that could be nice to have done

She's mine. Take a number.

haha, meh, i'm gonna see how far i can get with REST

You have no idea how hard it is to find a competent frontend dev, on here, that isn't already drowning in work.

I've gotten so desperate, that I've been doing it myself, to much hilarity. 🙄

I’ve been thinking about this, yes. Have a couple of my own ideas percolating. I also have a demo selective crawler set up to pick from and have some plans to give people previews and selections, essentially saving them from endless test articles.

it's an interesting idea, like nostr:npub1l5sga6xg72phsz5422ykujprejwud075ggrr3z2hwyrfgr7eylqstegx9z has been talking about with improving upon web of trust to count engagement data as well, and then you can add on top full text indexes and machine learning text graph analysis

and then also stuff like noticing idle follows, or follows that a user never engages with

nostr:npub176p7sup477k5738qhxx0hk2n0cty2k5je5uvalzvkvwmw4tltmeqw7vgup has been doing some work in this direction also

I liked the idea of essentially running a spam filter backward. Instead of marking things 💩, you 🌟 things, and it adjusts your filter.

Kind of like nostr:npub1utx00neqgqln72j22kej3ux7803c2k986henvvha4thuwfkper4s7r50e8 algo, but with the addition of examples, to the set of rules.

so it could use a bayesian filter as well, although you'd have to be able to tune its sensitivity

I’m a little obsessed with long form articles, so I have ideas for favorites and semantic search working together

I just went through my following list and realized how many I was following that have not posted for over a month and unfollowed them all. They were all part of my automatic onboarding. I did notice some kind of preference for those who were primal subscribers. It would be an interesting idea to have something set up where automatically unfollow people who have not posted after a certain amount of time.