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  • Henry Broadbent

Navigating the Algorithm

Explored by: Henry Broadbent (he/him)


I’m going to make a confession. I love Spotify Wrapped. 


There’s a handful of constants that seem to accompany me every year as summer approaches. I’ll be seized with a desire to ‘fix’ my sleep schedule, in order to join the hoards of well-adjusted people I know to be out parading on the waterfront while I drool on a pillow. I’ll start to think about what books to buy my family this Christmas (and try to remember exactly who I have already gifted a copy of My Family and Other Animals to). I’ll also start to shake off the shackles of seasonal depression, alongside everyone else in our chilly town. It is into this milieu of people newly armed with conversational ability and something approaching enthusiasm that Spotify Wrapped tends to drop. The perfect icebreaker, a conversational tool gifted to us from the digital ether, a corporate team building exercise/musical horoscope that ensures you have something to report, no matter how uneventful your winter.


Of course, this horoscope is built on a near-alarming amount of data—and the numbers don’t lie. This is part of the fun, as Wrapped quickly becomes apparent as a sort of self-actualisation test. Nothing unexpected about your top five artists? Congratulations! Your self image is accurate, and robust. Absolutely blindsided and embarrassed by the presence of The Smiths at #3? Go to therapy! 


Nowhere is this more true than in the hard figure of minutes listened, a stat that can get pretty dizzying if you’re a music junkie. As with the top 5 artists, it’s both the number itself, and whatever gap appears between expectation and reality, that’s telling. It can be hard to see a busy, stressful year quantified as a low number on your Wrapped. There is also, I’ve discovered, an upper figure (somewhere around 120,000 minutes) where people’s reaction to your ‘score’ begins to move from admiration to something approaching concern. Wait, how many minutes?


This is all to say that, as far as the online music streaming model goes, I’m in deep. I’ve got playlists going back to Year 10, group chats that revive each year to compare top songs and genre breakdowns, and a collaborative playlist for every workplace I’ve been in (shout out Coworker Music). However, I have noticed there seems to be a hard limit to the range of music Spotify’s algorithm is willing to serve up—once the service has decided it ‘knows’ your taste, this decision can quickly become a prison. Thankfully, you’ve got Salient to fix that for you, in a few hundred words. God we’re good. 


Alright, that damn algorithm. Happily, I’m oddly well equipped to help here, thanks to a couple of years in the trenches of Courtenay Place’s Little Waffle Shop, with access only to desktop Spotify on the till, and an endless parade of drunk revellers. It was a greasy and underpaid experience, but one that by necessity sharply honed my Spotify abilities—hearing the same cover of Harvest Moon every shift meant taking matters into my own hands. Thankfully, I can report it is possible to extract some true randomness and range from this sometimes cagey platform.


First stop: the search engine (desktop/web). Don’t be fooled by the explicit lack of an ‘advanced search’, because this thing has grunt. There’s a handful of modifier words you can use to change the game, making searches by genre, year, or even specific label, and combining phrases. AND, OR and NOT all work as modifier terms. An example: If you search “genre:house AND year:1995-1999” you’ll be greeted with a list of every song they play at Swimsuit. 


Looking for records released on Blue Note Records between 1985-7? Spotify has your back. Want to dig through the 1985 EMI catalogue, but you specifically don’t want any Radiohead? No worries. 


Next, hold off on feeding the machine too much. If you use your ‘liked songs’ feature, consider switching instead to building a catch-all playlist for that purpose. It’s a little bit laborious, but I promise the extra mahi is worth it—Spotify seems to put an awful lot of weight on that little plus button, and if you want it to stop sending you the same song again (and again and again and again), this seems the most surefire way to achieve that.


Last of all, artist bio’s and related artists! The bio is the one part of the platform over which musicians have much sway—sometimes they’ll be written by the group, you can often find interesting context for the music down there, and they can hold links to merch, tickets and more direct income. They’re also accompanied by a list of related artists. 


Now, before you inform me that this list is no different to what the algorithm might throw at you, you’re right—to a point. The artists you might find suggested below Phoebe Bridges (Julien Baker, Big Thief, etc) are the same ones that would likely come up on an artist radio. Dig deeper, though, and you can begin to use the ‘fans also like’ section as a network. If you’ve ever played a variation on those games that encourage you to find the fastest route between two seemingly disparate Wikipedia pages, you’ll understand how rapidly you can go ‘off track’. The concept is the same, and by building a queue and moving deeper into the ‘web’ of related artists, it’s possible to find yourself listening to something the algorithm would never have served up. 


Armed with some info you can keep your study playlists fresh, stay on the good side of your colleagues, and arrive next summer with a truly eclectic Wrapped to be proud of.


PS: Use Spotify as a music discovery service! Broaden your horizons! But, if you find something you really like, remember: small artists get $0.00173 per stream. Buy a record, score some merch, get the LP on bandcamp, and go to a gig! x


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