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Recommender Systems

Alaimo, Cristina and Kallinikos, Jannis (2019) Recommender Systems In: The Oxford Handbook of Media, Technology and Organization Studies. Oxford University Press (OUP).

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Recommender Systems.docx - Accepted version Manuscript

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Abstract

Personalization increasingly mediates the experience of users on the Web. Online platforms and organizations use personalization services to retain users, achieve longer user or customer engagement and, ultimately, higher profits. Cast in this light, personalization is a ubiquitous modality by means of which organizations seek to structure interaction with their users. Amazon, for instance, mediates the buying experience of its customers through computational systems that advance recommendations concerning relevant products to buy upon nearly every transaction. Similarly, Spotify uses the listening habits of its users to recommend tunes which they may find relevant to listen. In a rather different context, Facebook modulates its news feed to the interests of individual users by mapping each user’s ongoing interaction with his/her network of other users, and Google famously personalizes its search engine results, gathering, in turn, relevant information on the search habits of users.

Item Type: Book Section
Divisions : Faculty of Arts and Social Sciences > Surrey Business School
Authors :
NameEmailORCID
Alaimo, Cristinac.alaimo@surrey.ac.uk
Kallinikos, Jannis
Editors :
NameEmailORCID
Beyes, T.
Holt, R.
Pias, C.
Date : 2019
Copyright Disclaimer : © 2018 Oxford University Press (OUP). This is a draft of a chapter/article that has been accepted for publication by Oxford University Press in the forthcoming book 'The Oxford Handbook of Media, Technology and Organization Studies' edited by Beyes, Holt & Pias due for publication in 2019.
Additional Information : Requested for the reading list MAN3153
Depositing User : Clive Harris
Date Deposited : 24 Aug 2018 07:21
Last Modified : 11 Mar 2020 14:35
URI: http://epubs.surrey.ac.uk/id/eprint/849087

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