I made quiblr. It’s a lemmy client that includes a For You option

Hi, I created the Lemmy client Quiblr which includes a For You feed which constantly evolves with the types of posts you interact with. 100% private and on-device (i.e. no data leaves your device).

On quiblr, you can use the “For You” sort like any other sort option

Thanks for the feedback. I just pushed an update to Quiblr. This should be fixed now for PWA

I appreciate the offer! I have localization features in my pipeline. I’ll let you know

Ofc! Thanks for your support 💪

I just gave Quiblr an open source update. You can find GitHub can be found here

That is the long term vision. This has been just a passion project that I work on the side. But keeping it all react native has made it easier for me to manage 1 app for web, iOS, and Android.

I didn’t want to rush out a native version though. I want it to really utilize native functionality

Thanks! I’ll take a look

Great question. Preferably, I’m trying to keep all requests to the feedback page or the Ko-fi page

Speaking of which, I gave you a shoutout in the repo for your “Feeling Lucky” feature request!

Thanks! It took a good bit of work to bring it together into a clean, single working repository

Just a quick follow up here - I added a simple toggle setting to Quiblr that lets you flip the arrow order.

Apologies for the slow roll out, I had a big laundry list of updates in this latest release!

Notes! I’ll aim to add it to the next release. Thanks

Thank you so much! And I just made a note on the voting arrow order. I like the idea of making that an option in settings

And I can look into collapsing parent comments too. As you pointed out, I made it so just child comments collapse. The idea to collapse the parent comment never occurred to me lol

I’ll see if I can work both of these features into the next release.

Lots of great feedback. I’ll try to address each:

• I tried to differentiate voting vs. “like/dislike” for the algorithm as to not confuse users who think they are logged in. I can put more thought into how to make this a bit more intuitive
• Quiblr is built as a progress web app (PWA) so it uses native app components. The benefit is that it is faster and easier to manage multiple code bases. But the con is that it doesn’t have all the same benefits as HTML. I added an “open posts in new tab” feature in the settings
• I like the idea of added more body text in the post itself. My fear was that it would make the feed look too crowded, but I can take second look at it
• I love the tooltips idea
• The 3 dot ellipses has a Post Detail section for each post. Maybe this could be a good place to add the link back to the original Instance url.
• I like the scrollbar idea. I think this could make sense as an optional setting because I personally don’t prefer the scroll bar but I want to include it for users who do prefer it
• I added a refresh button for users using the PWA version (since they don’t have a refresh button in the browser). Maybe something like “pull down to refresh” could work on
• You should be able to press the “<” back button when viewing a community on mobile or just back in your browser. Both should take you back to your feed. Let me know if it isn’t working as intended
• I’ll have to see the API allows for removing downvoted items from feeds. I can try to get creative if needed

Edit: Added tooltips for post buttons + original url on the Post Detail page. I will continue to update this comment as I work through other additions in this list

Web based for now. IOS and Android apps are in the works!

Thanks a bunch! It took me a while to craft the solution to make sure it was both effective + private. I was originally inspired by Canopy. They built a news aggregator with private & personalized posts a few years back and the idea sat in my head.

To answer your question(s), there are quite a few signals that big tech uses to recommend content. Not all of them are privacy invasive (or at least they don’t HAVE to be). My approach was to do thorough research on the different signals used by big tech to make their recommendation engines, and just build ones that 1.) were possible given fediverse API limitations and 2.) private. I had to craft some novel approaches to make it work but I’m pretty happy with the outcome!

One of the biggest differences between the “big tech” approach and Quiblr’s is that most big tech does not keep data simply on your device. They store it in datacenters to build large social-webs to essentially cluster users (and push more relevant ads).

But I was able utilize many of the other signals used by big tech (e.g. communities you engage with, metadata of content you read, dwell time, post/comment/vote activity) and I designed it to work offline with no servers.

Edit: grammar