I ditched the algorithm for RSS

A good algorithm is a good thing. However what a good algorithm is for me is often different from what it is for those who maintain them. Outrage gets attention and sometimes it is needed, but there is a level of too much, and also a lot of outrage unfairly represents the issues and so it makes me mad even though if I understood the details I wouldn't be mad just concerned.

I want an algorithm that surfaces things of interest to me, then says "you have seen it all, go outside" (with an option of if I'm confined to a hospital bed to go on). Algorithm maintainers want me to keep scrolling for more ad dollars.

> I want an algorithm that surfaces things of interest to me, then says "you have seen it all, go outside" (with an option of if I'm confined to a hospital bed to go on).

[Acquire, or Employ your] good taste, sensibility & discipline.

Edit: For the record, "Employ your..." assumed that it if "good taste, sensibility & discipline" was not already acquired, it was already possessed and who I was responding to is able to put it to use.

Let those characteristics be your algorithm...or rather, your natural heuristic for living fair.

Has good faith met the end that it's said that chivalry saw?

You said what I wanted to say.

I think there is a niche market for tools that allow individuals to train their own recommendation systems.

> you have seen it all, go outside

Or "you've seen it all. Bored? Click here to let your friends know you're looking for something to do/see who else is bored". Or "Bored? X needs volunteers!" Or some other positive suggestion to try to prevent a "eh guess I'll doomscroll something else" reaction.

That would be such a killer feature. And it could find other friends in the area and that are also free. Not like Meta doesn't have some kind of model for all that data already probably.

Yes. I'd love to find other nerds into retro computing, UNIX, and pottery in my area without wading into groups or joining a forum. They know everything about me, match me up with some people I'd most likely get along with!

Bluesky is trying to figure out how to outsource algorithms and let you decide which to use.

Highly recommended podcast episode: https://oxide-and-friends.transistor.fm/episodes/scaling-blu...

Isn't this what ancient local BBSs did? Back in the 90's when in my teens/twenties that was how I found interesting local groups of people/organic raves (i.e. not ones organized by promoters) outside my established circles in Santa Cruz/the bay area. Also some of the most uncomfortable/awkward unsocial/nerdfest social evenings so not everything was a hit.

I'm guessing that there are now Discords that fill this niche?

> That would be such a killer feature.

"Alice, what if we made a button that improved overall human wellbeing, while somewhat reducing our ad-revenue and lowering the engagement-metrics we use to sell shares to investors?"

"*sigh* We've been over this, Bob: We only build features for customers--not cattle."

I'd like to see an RSS item-level recommendation / discovery algorithm driven by recommendations made by a cohort of people who have similar likes to me. I wish there was a standards-based to publish a stream of my "likes" from my feed reader, and to "consume" the "likes" of others. When I add somebody's blog to my feed reader I'd expect it to pick up their "likes" (much like how people used to have a "blog roll" on their own site) and begin to consume the "feeds" from the sites they "like". It reminds me a bit of PHP's "web of trust".

Hacker News, arguably, functions in this capacity for me now. The cohort is the entire population (since we all see the same item rankings), though.

You should read about OPML blogrolls [1], they are gaining traction in this space. Personally, I like the idea of manually exploring recommendations, so I built a browsable index [2]. But you can crawl the these as well and build all sorts of recommendations engines.

[1] https://opml.org/blogroll.opml

[2] https://alexsci.com/rss-blogroll-network/discover/feed-c550c...

A long long time ago before reddit, facebook, digg, twitter, etc, there was usenet. It worked a bit like reddit but subreddits were called news groups.

There were many front ends for usenet, called news readers.

My favourite was "nn" short for "no news".

It showed you posts in groups you're subscribed to, allowed you to post comments, etc.

When you had finished getting up to date it would EXIT and print:

No news. (Is good news)

What you are describing is similar to how https://LinkLonk.com works (my side project) - when you "like" a link you get connected to the RSS feeds that posted that link and other users that also liked it. Then you get content from feeds and users that you are connected to. The more links in common you have with a feed or a user the more weight their other links have.

There's been some conversation on Mastodon (and here) about its lack of algorithm

I really prefer my feed with no algorithm. I really like that it's just ordered by when it was posted, and if someone spams too much I'll remove them, and if my feed gets too much I'll curate it down a bit.

Ha! I had forgotten that message.Thank you for reminding me. I used to read comp.lang.lisp for the extensive and increasingly bizarre flame wars and for the wider philosophical discussions. Eventually I got to the point where I thought "OK I'm done now" and left and never went back.

You seem to be behind on English as spoken. From what I can reconstruct:

Algorithm (n) - a secretive set of systems, procedures and data that Big Tech uses to maliciously manipulate unsuspecting general public. Example usage: "Algorithm-free music discovery app for DJs"

I'm not joking, that example usage is taken from a live example.

The cool thing is: Its still there!

Yeah, it may be not as populated as in the 80s to mid 90s, but there are still enough active groups in usenet to waste uncounted hours every day...

Thanks for the blogroll love!

You can also see one in action on my blog's home page.

http://scripting.com/

And on a special site..

https://blogroll.social/

A blogroll is a kind of feed reader.

Do any of the web-based readers offer discovery based on matching your RSS list to other users' lists? Mine (Feedbin) doesn't, but I'd like it as an opt-in option.

Just put a chatbox at the end of the feed, that all the locals get dumped into when they also hit the end. Maybe based on IP or something. Grouped based on which articles you clicked on. "Hey, we think you guys will like eachother. Why don't you organize a meetup?"

If you want revenue, send them all to a nearby bar or other venue and work out a deal with that venue. "Hey, there's a bunch of Redditors and Joe's Bar right now! Take this coupon for 20% off and go meet them."

Such an algorithm would require plenty of data to be well trained, and I fear that the same crowd that would value such an algorithm, prioritises privacy too much.

Perhaps malicious algorithms and tracking have driven us too paranoid to even collaborate on an algorithm that actually serves us.

Here's what I do: - six 'links to top posts from the past week' links for subreddits/HN, in rotation. - a collection of RSS feeds from bloggers I've seen enough writing to recognize (and academic journals), which I check weekly

Every day is a focused collection of the most upvoted posts from one of those seven. It's hardly a perfect algorithm, but it at least disengages the worst instincts of FOMO. And the RSS feed can be seen as an escape hatch of sorts. If you really wanted to, you could try browsing /new once in a while as some kind of public penance or panning for gold.

edit: turns out the actual post is pretty close to this, with more RSS as a middleman. I just use Trello cards as rotating bookmarks, having given up on RSS being viable for anything other than the profitability of the RSS publisher.