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Recommendation Systems as Technologies of the Self: Algorithmic Control and the Formation of Music Taste

The article brings to light the use of recommender systems as technologies of the self, complementing the observations in current literature regarding their employment as technologies of ‘soft’ power. User practices on the music recommendation website last.fm reveal that many users do not only utili... Full description

Journal Title: Theory culture & society, March 2018, Vol.35(2), pp.3-24
Main Author: Karakayali, Nedim
Other Authors: Kostem, Burc , Galip, Idil
Format: Electronic Article Electronic Article
Language: English
Subjects:
ID: ISSN: 0263-2764 ; E-ISSN: 1460-3616 ; DOI: 10.1177/0263276417722391
Link: https://journals.sagepub.com/doi/full/10.1177/0263276417722391
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recordid: sage_s10_1177_0263276417722391
title: Recommendation Systems as Technologies of the Self: Algorithmic Control and the Formation of Music Taste
format: Article
creator:
  • Karakayali, Nedim
  • Kostem, Burc
  • Galip, Idil
subjects:
  • Algorithms
  • Care of the Self
  • Foucault
  • Last.Fm
  • Online Music Recommendation
  • Recommendation Systems
  • Technologies of the Self
  • Social Sciences (General)
ispartof: Theory, culture & society, March 2018, Vol.35(2), pp.3-24
description: The article brings to light the use of recommender systems as technologies of the self, complementing the observations in current literature regarding their employment as technologies of ‘soft’ power. User practices on the music recommendation website last.fm reveal that many users do not only utilize the website to receive guidance about music products but also to examine and transform an aspect of their self, i.e. their ‘music taste’. The capacity of assisting users in self-cultivation practices, however, is not unique to last.fm but stems from certain properties shared by all recommendation systems. Furthermore, unlike other oft-studied digital/web technologies of the self which facilitate ‘self-publishing’ vis-à-vis virtual companions in social media, recommender algorithms themselves can act as ‘intimate experts’, accompanying users in their self-care practices. Thus, recommendation systems can facilitate both algorithmic control and creative self-transformation, which calls...
language: eng
source:
identifier: ISSN: 0263-2764 ; E-ISSN: 1460-3616 ; DOI: 10.1177/0263276417722391
fulltext: fulltext
issn:
  • 0263-2764
  • 02632764
  • 1460-3616
  • 14603616
url: Link


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descriptionThe article brings to light the use of recommender systems as technologies of the self, complementing the observations in current literature regarding their employment as technologies of ‘soft’ power. User practices on the music recommendation website last.fm reveal that many users do not only utilize the website to receive guidance about music products but also to examine and transform an aspect of their self, i.e. their ‘music taste’. The capacity of assisting users in self-cultivation practices, however, is not unique to last.fm but stems from certain properties shared by all recommendation systems. Furthermore, unlike other oft-studied digital/web technologies of the self which facilitate ‘self-publishing’ vis-à-vis virtual companions in social media, recommender algorithms themselves can act as ‘intimate experts’, accompanying users in their self-care practices. Thus, recommendation systems can facilitate both algorithmic control and creative self-transformation, which calls...
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abstract

The article brings to light the use of recommender systems as technologies of the self, complementing the observations in current literature regarding their employment as technologies of ‘soft’ power. User practices on the music recommendation website last.fm reveal that many users do not only utilize the website to receive guidance about music products but also to examine and transform an aspect of their self, i.e. their ‘music taste’. The capacity of assisting users in self-cultivation practices, however, is not unique to last.fm but stems from certain properties shared by all recommendation systems. Furthermore, unlike other oft-studied digital/web technologies of the self which facilitate ‘self-publishing’ vis-à-vis virtual companions in social media, recommender algorithms themselves can act as ‘intimate experts’, accompanying users in their self-care practices. Thus, recommendation systems can facilitate both algorithmic control and creative self-transformation, which calls...

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lad01Theory, culture & society
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