More of the Same – On Spotify Radio


  • Pelle Snickars Umeå University



Spotify Radio, digital methods, music looping, bot intervention, reverse engineering


Spotify Radio allows users to find new music within Spotify’s vast back-catalogue, offering a potential infinite avenue of discovery. Nevertheless, the radio service has also been disliked and accused of playing the same artists over and over. We decided to set up an experiment with the purpose to explore the possible limitations found within “infinite archives” of music streaming services. Our hypothesis was that Spotify Radio appears to consist of an infinite series of songs. It claims to be personalised and never-ending, yet music seems to be delivered in limited loop patterns. What would such loop patterns look like? Are Spotify Radio’s music loops finite or infinite? How many tracks (or steps) does a normal loop consist of? To answer these research questions, at Umeå University’s digital humanities hub, Humlab, we set up an intervention using 160 bot listeners. Our bots were all Spotify Free users. They literally had no track record and were programmed to listen to different Swedish music from the 1970s. All bots were to document all subsequent tracks played in the radio loop and (inter)act within the Spotify Web client as an obedient bot listener, a liker, a disliker, and a skipper. The article describes different research strategies when dealing with proprietary data. Foremost, however, it empirically recounts the radio looping interventions set up at Humlab. Essentially, the article suggests a set of methodologies for performing humanist inquiry on big data and black-boxed media services that increasingly provide key delivery mechanisms for cultural materials. Spotify serves as a case in point, yet principally any other platform or service could be studied in similar ways. Using bots as research informants can be deployed within a range of different digital scholarship, so this article appeals not only to media or software studies scholars, but also to digitally inclined cultural studies such as the digital humanities.


Allen Anderson, Paul (2015): “Neo-Muzak and the Business of Mood”, Critical Inquiry 41:4, 811-840.

Bernhardsson, Erik (2013): “What data points does Spotify’s Radio feature use?” (Accessed 15/03/17).

Bernhardsson, Erik (2014): “Music Discovery at Spotify” erikbern/music-recommendations-mlconf-2014 (Accessed 15/03/17).

Bill (2014) (Accessed 15/03/17).

Chandra, Vikram (2013): Geek Sublime: Writing Fiction, Coding Software, London: Faber.

Dieleman, Sander (2014): “Recommending music on Spotify with deep learning” http:// (Accessed 15/03/17).

Dieleman, Sander, van den Oord, Aaron & Schrauwen, Benjamin (2013): “Deep con­tent-based music recommendation” file/4324567 (Accessed 15/03/17).

Fixmer, Andy (2012): “Spotify Said Developing Pandora-Like Online Radio Ser­vice”­loping-pandora-like-online-radio-service (Accessed 15/03/17).

Gehl, Robert W. (2014): Reverse Engineering Social Media. Software, Culture, and Political Economy in New Media Capitalism, Philadelphia: Temple University Press.

Gunnarsson Lorentzen, David (2016): Following Tweets Around Informetric method­ology for the Twittersphere, Borås: The Swedish School of Library and Information Science.

Hachman, Mark (2012): “Spotify to Take On Pandora With Radio Service” (Accessed 15/03/17).

hahndreas (2015): “The radio option sucks” comers-and-Contribution/The-radio-option-sucks/td-p/863585/page/4 (Accessed 15/03/17).

Friesinger, Günther & Herwig, Jana (2014) (eds.): The Art of Reverse Engineering, Bielefeld: Transcript.

Hietala, Heikki (2014): “Why do my Spotify radio sounds so repetitive?” Accessed 15/03/17).

Hu, Yajie. & Ogihara, Mitsunori (2011): “NextOne Player: A Music Recommendation System Based on User Behavior”, 12th International Society for Music Information Retrieval Conference, 103–108.

Kitchin, Rob (2016): “Thinking critically about and researching algorithms”, Infor­mation, Communication & Society, 24 February, 1-16.

Kjus, Yngvar (2016): “Musical exploration via streaming services: The Norwegian experience”, Popular Communication, 14: 3, 127-136.

Lamere, Paul (2014): “The Skip” (Accessed 15/03/17).

lehwark (2012): “Better Radio Algorithms”­sed-Ideas/Better-Radio-Algorithms/idi-p/107485 (Accessed 15/03/17).

Leijder Havenstroom, Bas (2015): “Why does my Spotify Radio play the same art­ists over and over for me?” (Accessed 15/03/17).

Lin, Ning, Tsai, Ping-Chia, Chen, Yu-An & Chen, Homer H. (2014): “Music Recom­mendation Based on Artist Novelty and Similarity”, Multimedia Signal Processing, IEEE 16th International Workshop, Jakarta, 1-6.

Madrigal, Alexis C. (2014): “How Netflix Reverse Engineered Hollywood” The Atlantic January 2 (Accessed 15/03/17).

Modell, Amanda (2015): “Mapping the Music Genome: Imaginative Geography in Pandora Internet Radio and the Genographic Project”, Media Fields Journal, 10, 1-13.

Morris, Jeremy Wade & Powers, Devon (2015): “Control, curation and musical expe­rience in streaming music services” Creative Industries Journal 2, 106-122.

Pasick, Adam (2015): “The magic that makes Spotify’s Discover Weekly playlists so damn good” Quartz December 21 (Accessed 15/03/17).

Popper, Ben (2015): “How Spotify’s Discover Weekly cracked human curation at internet scale”­ver-weekly-online-music-curation-interview (Accessed 15/03/17).

Quora (2016): “Spotify Radio” (Ac­cessed 15/03/17).

Resare, Noa (2013): “How does Spotify radio work”­es-Spotify-Radio-work (Accessed 15/03/17).

Seaver, Nick (2014a): “On Reverse Engineering. Looking for the cultural work of engineers”­ering-d9f5bae87812#.9tw36ldh1 (Accessed 15/03/17).

Seaver, Nick (2014b): “Knowing algorithms” seaverMiT8.pdf (Accessed 15/03/17).

Seaver, Nick (2016) (Accessed 15/03/17).

Shao Dingding, Bo & Tao Li, Wang (2009): “Music Recommendation Based on Acoustic Features and User Access Patterns” IEEE Transactions on Audio, Speech, and Language Processing 17:8,1602–1611.

Snickars & Mähler, Roger (2017): “SpotiBot -Turing Testing Spotify” Digital Hu­manities Quarterly forthcoming.

Spotify Radio (2016)­fy-radio/ (Accessed 15/03/17).

Tamar (2015): “The radio option sucks”­mers-and-Contribution/The-radio-option-sucks/td-p/863585/page/4 (Accessed 15/03/17).

tellure (2015): “‘Only play songs Spotify has never played before’ option for Radio” (Accessed 15/03/17).

The Echo Nest (2011): “The Echo Nest Powers Spotify Radio” http://blog.echonest. com/post/14311681173/spotify-radio-the-echo-nest (Accessed 15/03/17).

The Echo Nest (2014): “Spotify Acquires Echo Nest”­releases/spotify-acquires-echo-nest/ (Accessed 15/03/17).

Timberg, Scott (2016): “Spotify is making you boring: When algorithms shape mu­sic taste, human curiosity loses” Salon June 10 spotify_is_making_you_boring_when_algorithms_shape_music_taste_human_ curiosity_loses/ (Accessed 15/03/17).

Whitman, Brian (2012): “How music recommendation works - and doesn’t work”­tion-works-and-doesnt-work (Accessed 15/03/17).

xebec-us (2015): “The radio option sucks”­comers-and-Contribution/The-radio-option-sucks/td-p/863585/page/4 (Accessed 15/03/17).

zaliad (2016): “Better Radio Algorithms lead to better music” https://community.­ad-to-better-music/idi-p/1333406 (Accessed 15/03/17).




How to Cite

Snickars, P. (2017) “More of the Same – On Spotify Radio”, Culture Unbound, 9(2), pp. 184–211. doi: 10.3384/cu.2000.1525.1792184.



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