so I could have a frontend that scraped every comment and then every like of every comment in a community
Or you could do the same thing that https://lemvotes.org/ does and follow the communities and actors to build this database on a separate server, which then can be used by the client(s).
Have you considered taking the approach from https://phanpy.social/, and let the sorting algorithms on the client side?
Not only would make your work independent from Lemmy, it would give you complete freedom to choose how to implement this.
Lemmy account age and Github experience are absolute orthogonal data points, how is that even something to be brought as an argument?
If you want to suggest features or improvements, please take a look at the Github repository.
The solution is to go to subscribe to Reddit RSS feeds so that we find stuff to repost here.
(Only half-joking)
All the crypto stuff is opt-in.
Laudable effort, horrible execution.
It would be faster and easier to adopt any solution like this if it was implemented client-side.
Seems to be working fine now. My instance can find yours without any problems.
Can you just tell us what is your domain, so we can help you troubleshoot it?
Open source or GTFO. :)
Seriously, Lemmy is AGPL. Any client you do and any functionality you build on top of it must be AGPL as well.
Now I am confused, are you able to make changes to the Lemmy codebase? A fork? If you want to find a way to fund development, why not just work with the current team?
As a concept, it could be a valid approach. But you need to put actual numbers to see if things make sense:
I think you’ll see that as soon as you start asking people to put money and to feel like they “own” it, the demands will increase and so will the costs.
For reference, the one coop I am somewhat familiar is from Mastodon: cosocial.ca. Each member pays CA$50/year for an account. I think this is particularly too expensive. There are other cheaper “commercial” alternatives that charge less:
Ok, which part of “multiple metrics” is not clear here?
Every risk analysis will have multiple factors. The idea is not to always have an absolute perfect ranking system, but to build a classifier that is accurate enough to filter most of the crap.
Email spam filters are not perfect, but no one inbox is drowning in useless crap like we used to have 20 years ago. Social media bots are presenting the same type of challenge, why can’t we solve it in the same way?
Platforms like Reddit and Tumblr need to optimize for growth. We need to have growth, but it is does not be optimized for it.
Yeah, things will work like a little elitist club, but all newcomers need to do is find someone who is willing to vouch for them.
Just add “account age” to the list of metrics when evaluating their trust rank. Any account that is less than a week old has a default score of zero.
Why does have it to be one or the other?
Why not use all these different metrics to build a recommendation system?
Well, I am on record saying that we should get rid of one-dimensional voting systems so I see your point.
But if anything, there is nothing stopping us from using both metrics (and potentially more) to build our feed.
That would be only true if people only marked that they trust people that conform with their worldview.
The indieweb already has an answer for this: Web of Trust. Part of everyone social graph should include a list of accounts that they trust and that they do not trust. With this you can easily create some form of ranking system where bots get silenced or ignored.
Unfortunately, no. Mastodon makes no distinction between posts and comments (it is all a Note), so there is no way for a Lemmy server to notify a mastodon server only for posts.