65 lines
4.3 KiB
Plaintext
65 lines
4.3 KiB
Plaintext
%% title = "the ListenBrainz data set"
|
|
|
|
- I've been using [ListenBrainz](https://listenbrainz.org) as my primary way of keeping track of my listens for a couple years now---I
|
|
don't recall exactly when I created my account, as I've imported my listens from Spotify, but my music players have been pushing data to ListenBrainz for a while now either way.
|
|
|
|
- I made an account because I was dissatisfied with being tied to a single service for all my music.
|
|
especially since I've been listening to more and more music outside of streaming services, which means my listening data wouldn't show up in Spotify.
|
|
|
|
- I chose ListenBrainz over a proprietary service, because I like the idea of building a huge data set of what people are listening to.
|
|
and adding my own two drops of water to that data set feels really cool.
|
|
not only can my data be used for greater scientific purposes, but I can also use _my own data_ for _my own scientific purposes_.
|
|
|
|
- obviously there's the question of _data ownership_; and technically speaking, I don't _own_ my data on ListenBrainz.
|
|
but honestly I don't mind that so much, since it's an open source service, that lets me export my data whenever I want to.
|
|
|
|
- you can find my account [here][def:social/listenbrainz].
|
|
|
|
- below are some things I've done with my data, as well as ideas about what I could do with it in the future.
|
|
when I have the time, patience, and motivation, of course.
|
|
|
|
- :TODO: the importing of my listens from Spotify
|
|
|
|
- I've never published the code, but I wrote a little script that took my exported Spotify data (thanks, GDPR!) and imported it into ListenBrainz.
|
|
not without faults though. it'd be nice to write up more about it.
|
|
|
|
- :TODO: nerdsniped by Spotify Wrapped
|
|
|
|
- [it's this](https://github.com/liquidev/nerdsniped-by-spotify-wrapped); it'd be nice to write up some more about it.
|
|
|
|
- :TODO: a story told by a thousand tracks
|
|
|
|
- I'd like to use my data set to take my top 1000 most listened tracks, and sort them in chronological order---tracks
|
|
I listened to earliest come first---to generate a sort of _life's soundtrack._
|
|
|
|
+ I already have such a _curated_ playlist like this on Spotify, but I'm curious how such a playlist would look, were it generated from objective listen data.
|
|
|
|
- sans some inaccuracies of course, since Bogdan Raczynski's [boku mo wakaran](https://bogdanraczynski.bandcamp.com/album/boku-mo-wakaran) got imported all as one track.
|
|
this is because the individual tracks are untitled, and ListenBrainz failed to differentiate them, despite my Spotify data saying "Untitled 1," "Untitled 2," and so on, with track indices.
|
|
so I'd have to skip it, which is a real shame, since it's a pretty cool album.
|
|
|
|
- :TODO: diminishing listens, or longer attention span?
|
|
|
|
- in 2018, I listened to 25652 tracks.
|
|
in 2019, I listened to 34904 tracks.
|
|
in 2020, I listened to 29248 tracks.
|
|
in 2021 it was 24451, in 2022 it was 22437, and in 2023 it was 22002.
|
|
|
|
- we're already past half of 2024, and I'd only listened to 10536 tracks so far as of typing this.
|
|
if I keep up the same pace throughout the other half of the year, and if I'm doing my math correctly, that'd mean at the end of the year I will have listened to around 15000 tracks.
|
|
that's quite a bit less than 2023, isn't it?
|
|
|
|
- I wonder why the numbers are getting lower and lower each year.
|
|
is it because I listen to less music overall, or is it because I listen to longer music?
|
|
I strongly presume it's the former, as a lot of things have changed for me in 2024---I
|
|
moved out to live with my girlfriend, and that means spending more time on housework and other mundane things.
|
|
|
|
- until recently I didn't have a pair of good wireless headphones to listen to music while cooking, cleaning, or doing the laundry, so that reduced my listen count quite a bit.
|
|
|
|
- funny how in July there was a large spike of 1747 listens, where other months seem to be oscillating around 1000 listens on average.
|
|
I don't know what that was about.
|
|
|
|
- I do wonder where the 2000 listens per month from last year went though.
|
|
|
|
- either way, I'd like to derive a data set that's counted by _minutes listened_ to iron over this, similar to what I did with Spotify Wrapped in 2022.
|