Algorithmic Resonance: AI-Driven Curation, Musical Taste, Identity, and Global Cultural Flows
Main Article Content
Authors
Beijing Normal-Hong Kong Baptist University
Abstract
Algorithmic curation systems have become an important part of contemporary music platforms, mediating how listeners discover, classify, and engage with sound. This article examines how recommendation infrastructures on Spotify, TikTok, and Douyin participate in the organization of musical taste, identity negotiation, and transnational circulation. Bringing together platform studies, cultural sociology, and qualitative evidence from interviews, platform observations, and case-tracing materials, the study develops algorithmic resonance as a conceptual framework for explaining how engagement signals, platform optimization, and repeated exposure become linked in music culture. The analysis identifies three dynamics: path-dependent taste stabilization, optimization-oriented creative production, and affinity-based global circulation. Rather than claiming direct causal access to proprietary algorithms, the article offers an interpretive account of how platform-visible interfaces, creator practices, and user reflections reveal recurring feedback loops between behavior, visibility, and cultural value. It contributes to debates on algorithmic culture by showing that recommendation systems do not merely distribute music; they help organize the temporal, affective, and infrastructural conditions through which music becomes familiar, valuable, and socially meaningful.
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright remains with the author(s). All articles are published under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits use, sharing, adaptation, distribution, and reproduction in any medium or format, provided that appropriate credit is given to the original author(s) and the source, a link to the license is provided, and any changes are indicated.
How to Cite
References
Abidin, Crystal. 2021. “Mapping Internet Celebrity on TikTok: Exploring Attention Economies and Visibility Labours.” Cultural Science Journal 12, no. 1: 77–103. https://doi.org/10.5334/csci.140.
Aguiar, Luis, and Joel Waldfogel. 2021. “Platforms, Power, and Promotion: Evidence from Spotify Playlists.” The Journal of Industrial Economics 69, no. 3: 653–91. https://doi.org/10.1111/joie.12263.
Ananny, Mike, and Kate Crawford. 2018. “Seeing without Knowing: Limitations of the Transparency Ideal and Its Application to Algorithmic Accountability.” New Media & Society 20, no. 3: 973–89. https://doi.org/10.1177/1461444816676645.
Anderson, Ashton, Lucas Maystre, Ian Anderson, Rishabh Mehrotra, and Mounia Lalmas. 2020. “Algorithmic Effects on the Diversity of Consumption on Spotify.” In Proceedings of The Web Conference 2020, 2155–65. New York: Association for Computing Machinery. https://doi.org/10.1145/3366423.3380281.
Beer, David. 2017. “The Social Power of Algorithms.” Information, Communication & Society 20, no. 1: 1–13. https://doi.org/10.1080/1369118X.2016.1216147.
Bonini, Tiziano, and Alessandro Gandini. 2019. “‘First Week Is Editorial, Second Week Is Algorithmic’: Platform Gatekeepers and the Platformization of Music Curation.” Social Media + Society 5, no. 4: 1–11. https://doi.org/10.1177/2056305119880006.
Bourdieu, Pierre. 1984. Distinction: A Social Critique of the Judgement of Taste. Cambridge, MA: Harvard University Press.
Bucher, Taina. 2018. If... Then: Algorithmic Power and Politics. New York: Oxford University Press. https://doi.org/10.1093/oso/9780190493028.001.0001.
Cheney-Lippold, John. 2017. We Are Data: Algorithms and the Making of Our Digital Selves. New York: New York University Press.
Cole, Sebastian. 2024. “Exploring Users’ Algorithmic Knowledge and Reflexivity in a Music Streaming Context: A Critical Realist Approach.” Convergence: The International Journal of Research into New Media Technologies 30, no. 6: 2075–89. https://doi.org/10.1177/13548565241277379.
Couldry, Nick, and Ulises A. Mejias. 2019. The Costs of Connection: How Data Is Colonizing Human Life and Appropriating It for Capitalism. Stanford, CA: Stanford University Press.
Cunningham, Stuart, and David Craig. 2019. Social Media Entertainment: The New Intersection of Hollywood and Silicon Valley. New York: New York University Press.
Datta, Hannes, George Knox, and Bart J. Bronnenberg. 2018. “Changing Their Tune: How Consumers’ Adoption of Online Streaming Affects Music Consumption and Discovery.” Marketing Science 37, no. 1: 5–21. https://doi.org/10.1287/mksc.2017.1051.
Denzin, Norman K. 2012. “Triangulation 2.0.” Journal of Mixed Methods Research 6, no. 2: 80–88. https://doi.org/10.1177/1558689812437186.
Eriksson, Maria, Rasmus Fleischer, Anna Johansson, Pelle Snickars, and Patrick Vonderau. 2019. Spotify Teardown: Inside the Black Box of Streaming Music. Cambridge, MA: MIT Press. https://doi.org/10.7551/mitpress/10932.001.0001.
Fernández, Marta Ezquerra. 2024. “Efeitos da seleção algorítmica no gosto musical dos usuários do Spotify [Effects of Algorithmic Curation in Users’ Music Taste on Spotify].” RMd: Revista Multidisciplinar 6, no. 4: 125–38. https://doi.org/10.23882/rmd.24258.
Freeman, Sophie, Martin Gibbs, and Bjørn Nansen. 2022. “‘Don’t Mess with My Algorithm’: Exploring the Relationship between Listeners and Automated Curation and Recommendation on Music Streaming Services.” First Monday 27, no. 1. https://doi.org/10.5210/fm.v27i1.11783.
Freeman, Sophie, Martin Gibbs, and Bjørn Nansen. 2023. “Personalised but Impersonal: Listeners’ Experiences of Algorithmic Curation on Music Streaming Services.” In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, article 412, 1–14. New York: Association for Computing Machinery. https://doi.org/10.1145/3544548.3581492.
Gillespie, Tarleton. 2014. “The Relevance of Algorithms.” In Media Technologies: Essays on Communication, Materiality, and Society, edited by Tarleton Gillespie, Pablo J. Boczkowski, and Kirsten A. Foot, 167–94. Cambridge, MA: MIT Press. https://doi.org/10.7551/mitpress/9780262525374.003.0009.
Hallinan, Blake, and Ted Striphas. 2016. “Recommended for You: The Netflix Prize and the Production of Algorithmic Culture.” New Media & Society 18, no. 1: 117–37. https://doi.org/10.1177/1461444814538646.
Helberger, Natali, Kari Karppinen, and Lucia D’Acunto. 2018. “Exposure Diversity as a Design Principle for Recommender Systems.” Information, Communication & Society 21, no. 2: 191–207. https://doi.org/10.1080/1369118X.2016.1271900.
Hesmondhalgh, David, Raquel Campos Valverde, D. Bondy Valdovinos Kaye, and Zhongwei Li. 2023. The Impact of Algorithmically Driven Recommendation Systems on Music Consumption and Production: A Literature Review. UK Centre for Data Ethics and Innovation. https://ssrn.com/abstract=4365916.
Kaye, D. Bondy Valdovinos, Xu Chen, and Jing Zeng. 2021. “The Co-Evolution of Two Chinese Mobile Short Video Apps: Parallel Platformization of Douyin and TikTok.” Mobile Media & Communication 9, no. 2: 229–53. https://doi.org/10.1177/2050157920952120.
Kitchin, Rob. 2017. “Thinking Critically about and Researching Algorithms.” Information, Communication & Society 20, no. 1: 14–29. https://doi.org/10.1080/1369118X.2016.1154087.
Lobato, Ramon. 2019. Netflix Nations: The Geography of Digital Distribution. New York: New York University Press.
Morris, Jeremy Wade. 2020. “Music Platforms and the Optimization of Culture.” Social Media + Society 6, no. 3: 2056305120940690. https://doi.org/10.1177/2056305120940690.
Morris, Jeremy Wade, and Devon Powers. 2015. “Control, Curation and Musical Experience in Streaming Music Services.” Creative Industries Journal 8, no. 2: 106–22. https://doi.org/10.1080/17510694.2015.1090222.
Napoli, Philip M. 2019. Social Media and the Public Interest. New York: Columbia University Press.
Nieborg, David B., and Thomas Poell. 2018. “The Platformization of Cultural Production: Theorizing the Contingent Cultural Commodity.” New Media & Society 20, no. 11: 4275–92. https://doi.org/10.1177/1461444818769694.
Plantin, Jean-Christophe, Carl Lagoze, Paul N. Edwards, and Christian Sandvig. 2018. “Infrastructure Studies Meet Platform Studies in the Age of Google and Facebook.” New Media & Society 20, no. 1: 293–310. https://doi.org/10.1177/1461444816661553.
Poell, Thomas, David B. Nieborg, and Brooke Erin Duffy. 2022. Platforms and Cultural Production. Cambridge: Polity Press.
Poell, Thomas, David Nieborg, and José van Dijck. 2019. “Platformisation.” Internet Policy Review 8, no. 4. https://doi.org/10.14763/2019.4.1425.
Prey, Robert. 2018. “Nothing Personal: Algorithmic Individuation on Music Streaming Platforms.” Media, Culture & Society 40, no. 7: 1086–1100. https://doi.org/10.1177/0163443717745147.
Prey, Robert. 2020. “Locating Power in Platformization: Music Streaming Playlists and Curatorial Power.” Social Media + Society 6, no. 2: 2056305120933291. https://doi.org/10.1177/2056305120933291.
Raffa, Massimiliano, and Riccardo Pronzato. 2025. “The Social Life of an Optimised Song: Reconstructing the Networked Cycle of Digital Music-Making.” Popular Music 44, no. 1: 62–80. https://doi.org/10.1017/S0261143025000273.
Seaver, Nick. 2019. “Knowing Algorithms.” In digitalSTS: A Field Guide for Science & Technology Studies, edited by Janet Vertesi and David Ribes, 412–22. Princeton, NJ: Princeton University Press. https://doi.org/10.1515/9780691190600-028.
Srnicek, Nick. 2017. Platform Capitalism. Cambridge: Polity Press.
Striphas, Ted. 2015. “Algorithmic Culture.” European Journal of Cultural Studies 18, nos. 4–5: 395–412. https://doi.org/10.1177/1367549415577392.
Vaizman, Tal. 2023. “Music Mentors of the Streaming Era: From Algorithms to Influential Figures.” Journal of Applied Youth Studies 6, nos. 1–2: 45–66. https://doi.org/10.1007/s43151-023-00090-2.
van Dijck, José, Thomas Poell, and Martijn de Waal. 2018. The Platform Society: Public Values in a Connective World. New York: Oxford University Press.
Villermet, Quentin, Jérémie Poiroux, Manuel Moussallam, Thomas Louail, and Camille Roth. 2021. “Follow the Guides: Disentangling Human and Algorithmic Curation in Online Music Consumption.” In Proceedings of the 15th ACM Conference on Recommender Systems, 380–89. New York: Association for Computing Machinery. https://doi.org/10.1145/3460231.3474269.
Webster, James G. 2014. The Marketplace of Attention: How Audiences Take Shape in a Digital Age. Cambridge, MA: MIT Press.
Article Sidebar
Download
The qualitative data used in this study include anonymized interview excerpts, platform observations, and case-tracing materials. Due to participant confidentiality and ethical restrictions, the full dataset is not publicly available. Relevant anonymized materials may be made available by the author upon reasonable request.
This work is licensed under a Creative Commons Attribution 4.0 International License.