Publicações recentes por Nikita Braguinski (GTCC)

Nikita Braguinski, colaborador no Grupo de Teoria Crítica e Comunicação do CESEM, destaca duas publicações suas lançadas neste primeiro semestre de 2026:

— “Music Streaming as a Mediated Process: Algorithms and Assets”. Journal of the Royal Musical Association, 2026: 1–8. https://doi.org/10.1017/rma.2026.10068: “Online music streaming and the platforms that enable it are a relatively new phenomenon in music practice, at least when measured against the timescales of music history. They involve not only very specific and structurally decisive financial arrangements (multi-sided markets, financialization), but also depend deeply on technological affordances that did not exist in their current form less than a generation ago — most notably recommender systems. The two books at the centre of this review, Computing Taste: Algorithms and the Makers of Music Recommendation by Nick Seaver and Streaming Music, Streaming Capital by Eric Drott, together illuminate many non-obvious yet crucial structural conditions of contemporary music streaming as a networked, lived practice distributed across humans, technology, finance, and culture”.

— “Using music streaming data for research: A relational approach”. Popular Music, 2025: 420-426. https://doi.org/10.1017/S0261143025101220: “Online music streaming has emerged as a central mode of consumption in Europe and many other parts of the world, representing a distinct break from older forms of music media such as compact discs or broadcast radio. Instead of the one-to-many models that have historically dominated music dissemination – where an individual’s listening habits could only be guessed at through aggregate sales figures or broadcast audience estimates – streaming has introduced a one-to-one model. This shift, which gradually gained momentum during the last two decades (Drott 2024, p. 1), hinges on platforms and devices that also allow unprecedented observation of how individual listeners engage with recorded music. Consequently, hundreds of millions of people are now individually tracked in near-real time, generating vast amounts of granular data”.