I finally caved and filled the right sidebar in Soapbox FE.

@alex Have you considered adding a trending section to the side too? IMHO it might be better suited for the left than the right.

If you think it would clutter the UI you could make a tab for it next to the Notification section and give it its own page instead

@realcaseyrollins Yeah it’s a thing people ask for a lot, but nobody in Pleroma wants to do because Mastodon’s implementation caused a lot of problems.

I will probably add it at some point, with some configuration options. It will be hard though. There’s no way to query that data quickly, so we have to store a cache of all incoming tags and then sort them. Even Mastodon’s algorithm doesn’t order these tags properly, it has a minimum threshold (10 statuses) after which it takes the top 5 by order of insertion… so the most active hashtag might not even show up on the list.

@alex Interesting. I didn't know all of this.

I frankly believe that a single website to view trends, or perhaps work as an API, would be the best option. I feel like a script that reads all the toots in the timeline should be able to scan the hashtags and sort them fairly quickly. Right? Shouldn't be too hard to do in #JavaScript.

@realcaseyrollins For each new tashtag it discovers, it will get slower to sort the entire list. Also, what’s the cutoff point? We have to store a date with each hashtag too, and we want to count occurrences of that tag from today but not occurrences of that tag from yesterday. Sorting them and pruning the old ones is too slow to happen every time someone loads the trending panel. So we need multiple layers of cache with background processes that automatically update them.

Mastodon just prunes it at 12am midnight UTC every day. So if you ever visit in the morning and there’s no trends, that’s why. It’s not from the past 24 hours, it’s trends since 12am UTC.

@alex @realcaseyrollins 'trending tags' in twitter etc are heavily moderated. they are popular, but they are still a way to 'steer the crowd'. hashtags themselves aren't federated entities yet (they are kinda sorta literals) so it's hard to get a global views of them, so to make them anything useful, we'd have to moderate (that is, push) them, too. it's fine if that's what you want, suggest topics for people to follow. just never try to imagine that 'trending hashtags' are some kind of mindhive 'best of the best'.

@lain @realcaseyrollins Makes sense. In the case of Spinster I made trends local-only, and I think that brought some value, by makings tags like #bookclub easier to find (although we did also get #FreeSquiddy, which was not good).

There are probably better ways to increase discoverability. But I fear they will all have this problem of needing some manual curation.

@alex @realcaseyrollins i think with the fediverse's instance concept, curated tags aren't that bad (curation / restriction is kind of the reason you are on an instance anyway).

@lain @alex I really don't like the idea of curating trending hashtags, IMHO...I'd prefer it to just show what people are talking about. Local-only trends would be helpful for filtering things specific to the community tho

@realcaseyrollins @alex that usually doesn't work because people will game the system and just post a lot

@lain @alex Ain't that what antispam policies are for

@realcaseyrollins @alex it's just a really hard topic. you have to know what your goal is. usually, it's 'hey this is what people are talking about, maybe check it out'. it's easier to do this with curation than to rely on an automated system. otherwise, #animearmpits will always be extremely popular.

@lain @realcaseyrollins @alex Trends are waste of time and energy and do not work. Topics are good and work but you have to allow for the merging of Topics or, better yet, have admin approve Topics so no duplicates. eg. Covid and covid-19 and coronachan should not be 3 Topics (same problem with trends).

@derek @lain @alex I feel like an AI algorithm should be able to automatically lump #COVID with #COVID_19 by character similarity. I've done similar text matching in #Python before.