The Cambridge Companion to Music in Digital Culture 2019
DOI: 10.1017/9781316676639.006
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Shaping the Stream: Techniques and Troubles of Algorithmic Recommendation

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Cited by 43 publications
(7 citation statements)
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“…The related artists page. Digital platforms play a major role in reproducing inequalities, which have already existed in the offline music world through several mechanisms, partly through their recommendation systems (Bauer, 2019;Celma, 2010;Goldschmitt and Seaver, 2019). For this very reason, we concentrated on one of the recommendation types of Spotify.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…The related artists page. Digital platforms play a major role in reproducing inequalities, which have already existed in the offline music world through several mechanisms, partly through their recommendation systems (Bauer, 2019;Celma, 2010;Goldschmitt and Seaver, 2019). For this very reason, we concentrated on one of the recommendation types of Spotify.…”
Section: Methodsmentioning
confidence: 99%
“…Instead of owning recorded music in material formats, immaterial music formats are not owned but accessed by listeners through the cloud (Burkart, 2014). Streaming services offer music as a service, as a "utility" (Goldschmitt and Seaver, 2019) rather than selling individual music tracks. The platform ecosystem reproduces the inequalities and center-periphery dynamics of the cultural industries through their central position in the economy, the content distribution and consumption patterns they facilitate, and recommendation systems that manage the content flow and the user-interface interaction.…”
Section: Digital Music Platforms and Recommendation Systems As Spaces Of Inequality Reproductionmentioning
confidence: 99%
“…What has a listener liked in the past? A master algorithm orchestrates the sub-algorithms’ outputs together into an ‘ensemble’ (Goldschmitt and Seaver, nd) that makes a simple decision: What song should be played next?…”
Section: Hookedmentioning
confidence: 99%
“…The value of personalization for listeners is integral to the challenges represented by commercial data mining (Goldschmitt & Seaver, 2019;Prey, 2019). People tacitly accept unprecedented tracking of online behaviour (Goldschmitt & Seaver, 2019, p. 67), and while tracking user data is used to optimize recommendations to listeners, these data insights also represent assets for streaming platforms (Drott, 2018;Prey, 2019).…”
Section: Algorithms and Discovery: Algorithmic Valuementioning
confidence: 99%
“…Insights into how people see, use and value music streaming services complement existing efforts to conceptualize how these services 'see' and categorize users. A common argument is that music streaming services need to find ways to differentiate their services given that the catalogue differences are minimal (Goldschmitt & Seaver, 2019;Morris & Powers, 2015;Prey, 2019). I do not, however, examine whether music streaming services are successful in their attempts to differentiate their brand from their competitors, but treat music streaming services generically, with the proposition that experienced value and loyalty are likely connected.…”
Section: Introductionmentioning
confidence: 98%