87 lines
5.1 KiB
Plaintext
87 lines
5.1 KiB
Plaintext
%% title = "the ListenBrainz data set"
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% id = "01J73BSW7VS69RQ84XWRAEYEHV"
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- I've been using [ListenBrainz](https://listenbrainz.org) as my primary way of keeping track of my listens for a couple years now---I
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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.
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% id = "01J73BSW7VBGDHEYH2KERY66VY"
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- I made an account because I was dissatisfied with being tied to a single service for all my music.
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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.
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% id = "01J73BSW7VT509JW9R1EWV5V2P"
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- I chose ListenBrainz over a proprietary service, because I like the idea of building a huge data set of what people are listening to.
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and adding my own two drops of water to that data set feels really cool.
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not only can my data be used for greater scientific purposes, but I can also use _my own data_ for _my own scientific purposes_.
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% id = "01J73BSW7VVXN98C2X6BTDGWV4"
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- obviously there's the question of _data ownership_; and technically speaking, I don't _own_ my data on ListenBrainz.
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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.
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% id = "01J73BSW7VEA11HX4ANRVA8JNT"
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- you can find my account [here][def:social/listenbrainz].
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% id = "01J73BSW7VYBWPM3DZ08HGTRC6"
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- below are some things I've done with my data, as well as ideas about what I could do with it in the future.
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when I have the time, patience, and motivation, of course.
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% id = "01J73BSW7VTGN0ZXSXN206EACN"
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- :TODO: the importing of my listens from Spotify
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% id = "01J73BSW7V5EP9Y8GHG3MVTV01"
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- 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.
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not without faults though. it'd be nice to write up more about it.
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% id = "01J73BSW7VJ5C3SRGZR35H9CXA"
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- :TODO: nerdsniped by Spotify Wrapped
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% id = "01J73BSW7V8TA5SQKARPDR1AP4"
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- [it's this](https://github.com/liquidev/nerdsniped-by-spotify-wrapped); it'd be nice to write up some more about it.
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% id = "01J73BSW7VY08T1S2W7RG2BY26"
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- :TODO: a story told by a thousand tracks
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% id = "01J73BSW7VX1WCVZKVRME1WW3P"
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- I'd like to use my data set to take my top 1000 most listened tracks, and sort them in chronological order---tracks
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I listened to earliest come first---to generate a sort of _life's soundtrack._
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% id = "01J73BSW7VWJNCHC3X3WBJVMA5"
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+ 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.
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% id = "01J73BSW7VXYKVRBGY1RCVDWA8"
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- 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.
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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.
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so I'd have to skip it, which is a real shame, since it's a pretty cool album.
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% id = "01J73BSW7V9FNPCWXHBVDEDPBC"
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- :TODO: diminishing listens, or longer attention span?
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% id = "01J73BSW7VHTJ81WBRF2RT40PD"
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- in 2018, I listened to 25652 tracks.
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in 2019, I listened to 34904 tracks.
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in 2020, I listened to 29248 tracks.
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in 2021 it was 24451, in 2022 it was 22437, and in 2023 it was 22002.
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% id = "01J73BSW7VTJ6549Y74JGPVTWF"
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- we're already past half of 2024, and I'd only listened to 10536 tracks so far as of typing this.
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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.
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that's quite a bit less than 2023, isn't it?
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% id = "01J73BSW7V8QEM1P7ME5MR6VXX"
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- I wonder why the numbers are getting lower and lower each year.
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is it because I listen to less music overall, or is it because I listen to longer music?
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I strongly presume it's the former, as a lot of things have changed for me in 2024---I
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moved out to live with my girlfriend, and that means spending more time on housework and other mundane things.
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% id = "01J73BSW7VKG46GQAK3H2RPPAQ"
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- 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.
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% id = "01J73BSW7VR7H7HW7JZCFB18W4"
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- funny how in July there was a large spike of 1747 listens, where other months seem to be oscillating around 1000 listens on average.
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I don't know what that was about.
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% id = "01J73BSW7VCC5N7MQ705J4QM7Q"
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- I do wonder where the 2000 listens per month from last year went though.
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% id = "01J73BSW7VZ2T6DNQRK54TDSND"
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- 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.
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