Abstract

Algorithmic curation on streaming platforms has fundamentally reshaped the production, circulation, and 
consumption of cultural goods, thereby transforming contemporary taste cultures. This study examines how 
recommendation systems on platforms such as Netflix, Spotify, and YouTube mediate audience preferences, 
influence cultural capital, and structure patterns of content discovery. Drawing on cultural sociology, platform 
studies, and data-driven media analysis, the paper explores the mechanisms through which algorithms filter, 
sequence, and prioritize content, including personalization, similarity matching, popularity bias, and temporal 
dynamics.The analysis highlights the role of algorithmic curation in producing path dependence, reinforcing 
aesthetic norms, and fostering echo chambers, while also enabling new forms of cultural exploration and 
diversification. It further interrogates the implications for audience fragmentation, the reconfiguration of cultural 
capital, and the tension between mainstream visibility and niche discovery. Through comparative perspectives and 
case-based insights, the study demonstrates that while streaming platforms expand access to cultural goods, they 
simultaneously concentrate attention and standardize taste patterns. The paper concludes that algorithmic 
curation does not merely reflect audience preferences but actively constructs them, redefining agency for both 
creators and consumers. It calls for greater transparency, methodological innovation, and regulatory attention to 
address the cultural and ethical implications of algorithmically mediated consumption in the digital age.