[devit]

This seems potentially amazing and capable of replacing Google News and Reddit, although it might a while to achieve that.

How is it ranking stories?

It might be worth considering trying to optimize placement based on number of clicks and the time passing until the user goes back to using Idina (this is slightly privacy-intrusive, but unfortunately browsers allow this if JavaScript is enabled by listening for mouse move events etc., so might as well take advantage of it).

The website could use thumbnail images for the articles, and more colors and more contrast on the pages (have titles and clickable things stand out more).

It seems that most of the top articles should have a Reddit thread, but only very few have links to Reddit; also could link to HN.

The popular/followed/customized UI seems quite confusing. It might make sense to autofollow all defaults, and make "followed" the default and the current popular be "explore other topics". Also, the default should probably be customized, with the non-customized version being offered in another tab.

Might want a "since last visit" time range (which obviously needs to be intelligent and ignore things like refreshes, maybe make it "since last visit on day XX time YY" so the user knows right away if it makes sense).

Should consider removing the "star rating" from customization, which is very hard/impossible to assign (is this worth 2 or 3 stars? how do I decide that?), and instead let users customize by ordering articles (up/down arrows + drag&drop), which is natural and easy.

Maybe consider copying Google News' click-to-expand mechanism.

[gerner]

I also struggled with the star rating, especially in my first few days. But at some point I just got over it. After a couple of weeks using it I'm just rating stuff without too much care and it seems pretty reasonable.

I think of the Netflix scale: 1 == terrible, never show me stuff like this in this topic (I think this is actually their threshold for exclusion from a topic) 2 == on topic, but but I don't like it 3 == this is OK, but I'd rather have something else 4 == good, solid content I'd be happy reading just this stuff 5 == wow, this is great, if it comes up it better be #1

@idina_news @_b can you confirm that ratings are _only_ applied in topic? (they don't leak to other topics)

[idina_news]

Can confirm; ratings are per-topic.

[idina_news]

These are great ideas. I'll need to ponder some of them a bit, although a few immediate thoughts are below. If you have any thoughts in the future, my email is [e-mail] (and _b is [e-mail]).

Like _b mentioned below, stories are ranked by ML fitting a bunch of signals and the article text to a user's ratings.

Usage metrics is something we want to figure out how to use well. Currently we track them, but don't use them.

Confession regarding images/colors/contrasts/etc: neither of us are UI people. It is something we struggle with, so doubly appreciate the feedback here. Will try to improve this soon.

Regarding some missing links to reddit, are there good threads on reddit we should be linking to for them, or has reddit just not picked them up? Our algorithms try to find every related reddit thread to a story, although they can make mistakes.

Regarding autofollowing all defaults -- it's tricky. We used to do this, and got feedback that people didn't link having to unfollow a bunch of topics when they created an account. Exactly how to package the experience is an open question, one that is complicated by the desire to have a good logged-out experience that transitions as smoothly to the logged-in experience as possible. Point being, you hit on a good issue here that we don't yet have a perfect answer to.

'Since last visit' time range sounds neat. Will look into adding.

Re: star ratings -- manually ordering articles (this should rank above that) or having up/down arrows for each article are also natural ways to provide ranking feedback. A big concern of ours here is the ability for a user to have a clean mental model of their own feedback over a long period of time. For example, feedback in the form of up/down arrows comes necessarily in the context of a specific set of articles shown at a specific time. If someone wants to review their feedback in aggregate, it might be difficult to represent it all in one place in a way that's easy to understand. On the other hand, your criticism of it is also correct. Adding additional ways to make training data, or changing how we do this, is something we are really interested in getting right.

[Alphasite_]

Honestly reddits value is more in comments, communities and categorisation than as an aggregator.