More of the Same – On Spotify Radio

Abstract

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.Snickars, Pelle: "More of the Same-On Spotify Radio", Culture Unbound, Volume 9, issue 2, 2017: 184-211. Published by Linköping University Electronic Press: http://www.cultureunbound.ep.liu.se

‘Melodies wander around as ghosts’: on Playlist as cultural form

“…71 This seems at the very least to imply a dubious definition of friendship one study of Spotify established an exaggerated ability to recommend music by its playlists. 72 In any event, the explorer subject fantasised here projects an equally imagined relation to hardware; the iconography of 'folder', 'desktop' and 'library' divorces the visual from the mechanic, and serves a broader mystification of all its forms of labour: from mining and assembly to coding and installation. 73 But if the interface thrusts an increasingly obsolete pre-digital world onto the screen, we can also discern a projection of the ontology of the computer back onto the music.…”

Problematic Machine Behavior: A Systematic Literature Review of Algorithm Audits

“…Furthermore, Metaxa et al [110] observed "virtually no difference" in the distribution of source partisanship between queries for Democrats versus Republicans. Shifting the focus beyond just the "blue links, " Hu et al [80] [144] 2016 Sock puppets Mapping Google Eslami et al [55] 2017 Direct scrape Search Booking.com Kulshrestha et al [94] 2017 Direct scrape Search Twitter Google Snickars [143] 2017 Sock puppets Recommendation Spotify Robertson et al [136] 2018 Crowdsourcing Search Google Andreou et al [6] 2018 Crowdsourcing Advertising Facebook Bechmann and Nielbo [16] 2018 Crowdsourcing Recommendation Facebook Puschmann [129] 2018 Crowdsourcing Search Google Chakraborty and Ganguly [25] 2018 Sock puppets Recommendation New York Times Courtois et al [32] 2018 Crowdsourcing Search Google Weber and Kosterich [158] 2018 Code Recommendation Not specified Kulshrestha et al [95] 2018 Direct scrape Search Google Twitter Rieder et al [135] 2018 Direct scrape Search YouTube Lurie and Mustafaraj [103] 2019 Direct scrape Recommendation Google Trielli and Diakopoulos [149] 2019 Direct scrape Search Google Moe [115] 2019 Direct scrape Search YouTube Metaxa et al [110] 2019 Direct scrape Search Google…”

Personaliserte anbefalinger og musikalsk mangfold– en umulig kombinasjon?

“…Synliggjøring dreier seg om hvordan tjenestene sorterer, filtrerer og presenterer katalogene sine. I forlengelsen av algoritmisk synlighet har derfor strømmetjenestenes egenskap som tilbydere av musikkanbefalinger fått en økt betydning (Chodos, 2020;Snickars, 2017;Seaver, 2019). Tjenestenes dreining fra å (i sin reneste form) vaere en distribusjonsplattform av kulturelt innhold, til å bli en «anbefalingsmaskin» -som utover den ubegrensede tilgangen tilbyr publikum veiledning -representerer en såkalt «kuratorial vending» (Eriksson, Fleischer, Johansson, Snickars & Vonderau, 2019;Sellar, 2014;Chodos, 2020), som setter «verden i system» og avlaster publikum «byrden ved å velge» (Maasø, 2016;Kiberg, 2018).…”

“…Blant de mest alarmerende er idéen om at personalisering skaper filterbobler (Pariser, 2011). Dette refererer til en tilstand av intellektuell isolasjon som oppstår når algoritmer filtrerer og synliggjør innhold kun basert på brukshistorikk: I stedet for å bli presentert for en bredde av sjangre og stiler, får du «mer av det samme» (Snickars, 2017). Pariser hevder at det finnes en rekke utilsiktede konsekvenser av det å havne i en filterboble, hvor saerlig den begrensede utvekslingen av idéer, perspektiver og innhold som viker fra ens egne preferanser, i verste fall virker som en trussel mot demokratiet (se Bozdag, 2013;Gillespie, 2016;Pariser, 2011) eller skaper devaluerende effekter på kulturell produksjon (Wolf, 2016).…”

“…Slik har overfloden av innhold skapt en «oppmerksomhetsøkonomi» (Davenport & Beck, 2001), hvor strømmetjenestenes mål er å holde på brukernes oppmerksomhet lengst mulig. Personalisert anbefaling av innhold har slik vokst seg fram som en plausibel og «nyttig» strategi, hvor informasjon om publikum og deres personlige preferanser, skreddersyr brukeropplevelsene (Wolf, 2016;Kitchin, 2017;Snickars, 2017). Samtidig stiller stadig flere spørsmål vedrørende de effekter disse anbefalingsmotorene har på musikkulturen, og analyser som peker mot ensretting og tap av mangfold har i økende grad dominert akademisk litteratur de siste årene (se Mulligan, 2014;Maasø, 2016;Snickars, 2017;Wikström, Moreau & Borreau 2018).…”