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Popular Music Studies

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Popular Music Studies

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Research Frontiers in Algorithmic Curation and Streaming Playlist Ecosystems

Examines how machine learning algorithms shape music discovery, artist visibility, and listener preferences on streaming platforms like Spotify and Apple Music.

Algorithmic Serendipity: Discovery Versus Predictability in Streaming

Playlist Homogenization and Genre Boundary Dissolution

Machine Learning Taste Regimes and Cultural Gatekeeping

Echo Chambers in Personalized Music Recommendation Systems

Algorithmic Payola: Commercial Bias in Automated Curation

Sonic Fingerprinting and Micro-Genre Proliferation

Listener Agency and Algorithmic Autonomy in Playlist Construction

Cold Start Problems and Emerging Artist Discoverability

Affective Computing: Mood Detection and Emotional Playlist Engineering

Temporal Dynamics of Viral Algorithmic Amplification in Music

All Popular Music Studies PhD categories