<![CDATA[Background: With 230 million internet users, Indonesia has become one of the world’s largest markets for new media streaming platforms, whose algorithmic recommendation systems now mediate the musical encounters of millions of young listeners. Purpose: This study examines how algorithmic recommendation mechanisms on new media streaming platforms shape music taste formation and cultural identity expression among Generation Z in Indonesia, and proposes a conceptual model for analyzing these processes in Global South contexts. Methods: The study is a conceptual, literature-grounded Platform Analysis. No primary empirical data were collected from users, and no interface walkthroughs or API-based platform audits were conducted. Five platforms (Spotify, YouTube Music, TikTok, Apple Music, and JOOX) were examined across four analytical dimensions through a thematic synthesis of peer-reviewed scholarship (Scopus, Web of Science, Google Scholar, and SINTA), publicly available platform documentation, and industry data. Results: The synthesis identifies four interlocking mechanisms: (1) hybrid editorial–algorithmic gatekeeping that localizes selectively, (2) datafied taste feedback loops, (3) unequally distributed digital capital, and (4) hybrid but bounded identity work. These are integrated into a Dual-Loop Model of Platform-Mediated Musical Identity, which couples an individual taste loop with a cultural visibility loop in which data-poor repertoires, such as many traditional regional genres, remain less discoverable. Conclusion: Streaming algorithms are not neutral tools; they encode taste hierarchies and co-produce the cultural identities of Indonesian youth, who retain real but bounded agency. Implications: The model and its four propositions offer a framework for empirical testing through interviews, ethnography, interface walkthroughs, and computational audits, and inform cultural policy and digital media literacy education.]]>
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