local stats.
currently there is either personal statistics or there is global statistics (which is worldwide) im more curious for local statistics (my country or village)
local stats.
currently there is either personal statistics or there is global statistics (which is worldwide) im more curious for local statistics (my country or village)
A post was split to a new topic: Feedback wanted: Pulling ListenBrainz stats into MusicBrainz
Probably shouldn’t happen. Storing location data is RGPD protected, and the least you touch that stuff the better
i’m not saying we need to fetch the location of the user and that sort of stuf. but maybe just have a way to filter and see stats per country or village.
where the usere selects the country or village. (we don’t need to store where the user is)
Well how are you going to get calculate the stats if you don’t know where the users are from?
it is in my profile Editor “sanojjonas” - MusicBrainz
but i guess it is just an opt-in type of deal…
if you don’t have a location i guess you’re listens only count for the worldwide stuff…
FYI there is a ticket regarding adding location data, with some notes and comments:
I don’t know if it was mentioned before, but I’d really like to have genre pages available on LB. I have some ideas for those pages:
something similar to this https://everynoise.com/ ?
To do this, you need to hang a white sheet on the wall and use a projector to display it on it.
Yes! We’ve been talking about a genre tree (we call it genre explorer) which a few of us have been daydreaming about
I really wan tot see it happen too, and ansh has started working on it.
It will most likely resemble our existing music neighborhood feature using the hierarchical data from MusicBrainz, rather than how everynoise presents it all in one page .
A genre page is also something we’ve discussed, and would be a great place for this genre explore to live (like we have the music neighborhood graph on artist pages)
Edit: I created a ticket for the genre page, which we didn’t have: https://tickets.metabrainz.org/browse/LB-1691
The last blog post and Spotify’s api deprecation leaves a big hole related to track audio analysis. With AcousticBrainz shutdown there is simply no alternative right now, it would be great to have something similar in ListenBrainz and picard.
I mean, if there is a perfect moment for it, it’s now. There are thousands of developers looking for a replacement…
For now the best thing we have is MB’s tags…
But that’s not good enough. It requires user input, which means most releases are missing tags. It’s also pretty subjective…
I have also seen so mockups for mood classification, but unless some automatic data fetching is done, I see no future for that. The only way to offer an alternative to Spotify or other APIs is by providing audio features, automatic genre classification, automatic mood retrieval, etc.In top of that you may add user tags and input, for sure (*).
(*) For ex. genre classification is pretty good using AI, audio features or Essentia models right now; at least for basic genres (rock, jazz, electronic, …). In top of that, you may use subgenres provided by users.
I would really love to see this feature implemented. I poked around in the settings for an embarrassingly long time before I realized it wasn’t possible.
this has probably been suggested before, but i think it would be cool if i knew who i am looking at when browsing profiles, like top 10 user’s genres or at least artists
would be cool if likes/loves data could be sync’ed with listenbrainz.
as of right now, every time i like something in spotify or my navidrome library, i have to come to listenbrainz and click “love” on the same track.
i’m a new user, so maybe i’ve missed something to set this up. any help would be appreciated. thanks
For now there’s Elbisaur although it’s not tested with the new export version.
A native one would be great but at least we got something-ish
For navidrome, I think this would be a navidrome thing. Like you need to request it with their devs. Jellyfin has support for this through its ListenBrainz plugin
Thanks! I’ll have to check it out more thoroughly tonight, but upon first glance, it looks a little complex.