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Studying Playlist Cultures with Qualitative Digital Methods

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Existing research highlights that playlists sit at the heart of the platform economy of digital music streaming. Characterised by a combination of editorial and algorithmic logics, playlists today represent for many users the main means to consume music, as well as a key component of platforms’ data-driven accumulation model. This chapter investigates playlist production and consumption practices by music streaming platform users in Italy. To this end, it experiments with an original combination of traditional qualitative research, consisting in 5 focus groups with Spotify listeners aged 19-25, and the use of an innovative software, SpotiGeM Hub, that queries the Spotify API to collect playlist features and metadata following digital methods principles. Our study evidences the existence of a spectrum of playlist production and consumption practices that blends genre-based listening habits, anchored in conventional music categories, with a more fluid set of practices that prioritize moods and the social situations in which listening happens. The chapter critically reflects on these findings, discussing the advantages and disadvantages that derive from combining qualitative research and digital data collection for the study of ‘platformized’ music consumption.

Keywords: digital methods ; focus groups ; genre ; mood ; music platforms ; playlist ; situation ; Spotify ; SpotiGeM

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Studying Playlist Cultures with Qualitative Digital Methods
Intellect , 670 (2025); https://doi.org/10.1386/9781835951033_42
/content/books/9781835951033.c40
/content/books/9781835951033.c40
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References

  1. Acker, Amelia and Kreisberg, Adam (2020), ‘Social media data archives in an API-driven world’, Archival Science, 20:2, pp. 105–23.
     [Google Scholar]
  2. Airoldi, Massimo (2021a), ‘Digital traces of taste: Methodological pathways for consumer research, Consumption Markets & Culture, 24:1, pp. 97–117.
     [Google Scholar]
  3. Airoldi, Massimo (2021b), ‘The techno-social reproduction of taste boundaries on digital platforms: The case of music on YouTube’, Poetics, 89, p. 101563.
     [Google Scholar]
  4. Airoldi, Massimo , Beraldo, Davide and Gandini, Alessandro (2016), ‘Follow the algorithm: An exploratory investigation of music on YouTube’, Poetics, 57, pp. 1–13.
     [Google Scholar]
  5. Arvidsson, Adam , Caliandro, Alessandro , Airoldi, Massimo and Barina, Stefania (2016), ‘Crowds and value: Italian directioners on Twitter’, Information, Communication & Society, 19:7, pp. 921–39.
     [Google Scholar]
  6. Bainotti, Lucia (2021), ‘Striving for conspicuousness: How micro-influencers construct and display social status on Instagram’, Ph.D. dissertation, Turin–Milan: NASP – University of Turin-University of Milan.
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  7. Barr, Kenneth (2013), ‘Theorizing Musical Streaming: Preliminary Investigations,’ Scottish Music Review, 3, pp. 1–20, https://scottishmusicreview.org/Articles/3/Barr%3A%20Theorizing%20Music%20Streaming%3A%20Preliminary%20Investigations.pdf. Accessed 7 January 2025.
  8. Bonini, Tiziano , Caliandro, Alessandro and Massarelli, Alessandra (2016), ‘Understanding the value of networked publics in radio: Employing digital methods and social network analysis to understand the Twitter publics of two Italian national radio stations’, Information, Communication & Society, 19:1, pp. 40–58.
     [Google Scholar]
  9. Bonini, Tiziano and Gandini, Alessandro (2019), ‘“First week is editorial, second week is algorithmic”: Platform gatekeepers and the platformization of music curation’, Social Media+Society, 5:4, pp. 1–11, https://doi.org/2056305119880006.
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  10. Bonini, Tiziano and Gandini, Alessandro (2020), ‘The field as a black box: Ethnographic research in the age of platforms’, Social Media+Society, 6:4, pp. 1–10, https://doi.org/2056305120984477.
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  11. Brackett, David (2016), Categorizing Sound: Genre and Twentieth-Century Popular Music, Oakland, CA: University of California Press.
     [Google Scholar]
  12. Bucher, Taina (2018), If … Then: Algorithmic Power and Politics, Oxford: Oxford University Press.
     [Google Scholar]
  13. Burkart, Patrick (2014), ‘Music in the cloud and the digital sublime’, Popular Music and Society, 37:4, pp. 393–407.
     [Google Scholar]
  14. Caliandro, Alessandro (2021), ‘Repurposing digital methods in a post-API research environment: Methodological and ethical implications’, Italian Sociological Review, 11:4S, pp. 225–42.
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  15. Caliandro, Alessandro and Gandini, Alessandro (2017), Qualitative Research in Digital Environments: A Research Toolkit, London: Routledge.
     [Google Scholar]
  16. Caliandro, Alessandro , Gandini, Alessandro , Bainotti, Lucia and Anselmi, Guido (2024), The Platformization of Consumer Culture: A Digital Methods Guide, Amsterdam: University of Amsterdam Press.
     [Google Scholar]
  17. DeNora, Tia (2000), Music in Everyday Life, Cambridge: Cambridge University Press.
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  18. Eriksson, Maria (2020), ‘The editorial playlist as container technology: On Spotify and the logistical role of digital music packages’, Journal of Cultural Economy, 13:4, pp. 415–27.
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  19. Eriksson, Maria , Fleischer, Rasmus , Johansson, Anna , Snickars, Pelle and Vonderau, Patrick (2019), Spotify Teardown: Inside the Black Box of Streaming Music, Cambridge, MA: MIT Press.
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  20. Fabbri, Franco (2012), ‘How genres are born, change, die: Conventions, communities and diachronic processes’, in S. Hawkins (ed.), Critical Musicological Reflections, Aldershot: Ashgate, pp. 179–91.
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  21. Fern, Edward (2001), Advanced Focus Group Research, London: Sage.
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  22. Freelon, Deen (2018), ‘Computational research in the post-API age’, Political Communication, 35:4, pp. 665–68.
     [Google Scholar]
  23. Galloway, Kate , Goldschmitt, K. E. and Harper, Paula (2020), ‘Guest editors’ introduction: Platforms, labor, and community in online listening’, American Music, 38:2, pp. 15–30, https://doi.org/10.5406/americanmusic.38.2.0125.
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  24. Gaiser, Ted (2008), ‘Online focus groups’, in N. G. Fielding , R. M. Lee and G. Blank (eds), The SAGE Handbook of Online Research Methods, Los Angeles: Sage, pp. 290–306.687
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  25. Holt, Fabian (2007), Genre in Popular Music, Chicago, IL: University of Chicago Press.
     [Google Scholar]
  26. Johnson, Tom (2020), ‘Chance the rapper, Spotify, and musical categorization in the 2010s’, American Music, 38:2 (Summer), pp. 176–96.
     [Google Scholar]
  27. Lena, Jennifer (2012), Banding Together: How Communities Create Genres in Popular Music, Princeton, NJ: Princeton University Press.
     [Google Scholar]
  28. Midia Research (2022), ‘Music subscriber market shares Q2 2021’, 18 January, https://www.midiaresearch.com/blog/music-subscriber-market-shares-q2-2021. Accessed 24 May 2022 .
  29. Morris, Jeremy Wade (2015), ‘Curation by code: Infomediaries and the data mining of taste’, European Journal of Cultural Studies, 18:4&5, pp. 446–63.
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  30. Morris, Jeremy Wade and Powers, Devon (2015), ‘Control, curation and musical experience in streaming music services’, Creative Industries Journal, 8:2, pp. 106–22.
     [Google Scholar]
  31. Nuttall, Peter , Arnold, Sally , Carless, Luke , Crockford, Lily , Finnamore, Katie , Frazier, Richard and Hill, Alicia (2011), ‘Understanding music consumption through a tribal lens’, Journal of Retailing and Consumer Services, 18:2, pp. 152–59.
     [Google Scholar]
  32. Poell, T., Nieborg, D. B. and Duffy, B. E. (2021), Platforms and Cultural Production. London: Wiley & Sons.
  33. Pichl, Martin , Zangerle, Eva and Specht, Gunther (2016), ‘Understanding playlist creation on music streaming platforms’, 2016 IEEE International Symposium on Multimedia (ISM), San Jose, CA, 11–13 December, pp. 475–80, https://doi.org/10.1109/ISM.2016.0107, https://ieeexplore.ieee.org/document/7823674. Accessed 7 January 2025.
     [Google Scholar]
  34. Prey, Robert (2020), ‘Locating power in platformization: Music streaming playlists and curatorial power’, Social Media+Society, 6:2, pp. 1–11, https://doi.org/2056305120933291.
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  35. Prey, Robert , Esteve Del Valle, Marc and Zwerwer, Leslie (2022), ‘Platform pop: Disentangling Spotify's intermediary role in the music industry’, Information, Communication & Society, 25:1, pp. 74–92, https://doi.org/10.1080/1369118X.2020.1761859.
     [Google Scholar]
  36. Rogers, Richard (2009), The End of the Virtual: Digital Methods, Amsterdam: Amsterdam University Press.
     [Google Scholar]
  37. Rogers, Richard (2013), Digital Methods, Cambridge, MA: MIT Press.
     [Google Scholar]
  38. Silverman, David (2020), Qualitative Research, London: Sage.
     [Google Scholar]
  39. Small, Christopher (1998), Musicking: The Meanings of Performing and Listening, Middletown, CT: Wesleyan University Press.
     [Google Scholar]
  40. Venturini, Tommaso and Rogers, Richard (2019), ‘“API-based research” or how can digital sociology and journalism studies learn from the Facebook and Cambridge Analytica data breach’, Digital Journalism, 7:4, pp. 532–40.
     [Google Scholar]
  41. Villermet, Quentin , Poiroux, Jeremie , Moussallam, Manuel , Louail, Thomas and Roth, Camille (2021), ‘Follow the guides: Disentangling human and algorithmic curation in online music consumption’, RecSys '21: Proceedings of the 15th ACM Conference on Recommender Systems, Amsterdam, 27 September–1 October 2021, New York: Association for Computing Machinery, pp. 380–89.
     [Google Scholar]
  42. Werner, Ann (2020), ‘Organizing music, organizing gender: Algorithmic culture and Spotify recommendations’, Popular Communication, 18:1, pp. 78–90.
     [Google Scholar]
  43. Willis, Paul (1978), Profane Culture, London: Routledge.
     [Google Scholar]
  44. YouGov (2021), ‘The most popular music streaming platforms in key markets globally’, 19 March 2021, https://today.yougov.com/entertainment/articles/34803-services-used-stream-music-poll. Accessed 24 May 2022 .

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