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Title: Making it personal : web users and algorithmic personalisation
Author: Kant, Tanya
ISNI:       0000 0004 5992 3758
Awarding Body: University of Sussex
Current Institution: University of Sussex
Date of Award: 2016
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This thesis investigates how web users negotiate and engage with contemporary algorithmic personalisation practices; that is, practices which seek to infer (via data tracking mechanisms and other algorithmic means) a user's habits, preferences or identity categorisations in order to ‘make personal' some component of that user's web experience. Drawing on thirty-six semi-structured interviews, I employ a qualitative methodology that seeks to bridge the gap between critical theorisations of algorithmic personalisation and the negotiations of web users themselves who encounter algorithmic personalisation in everyday life. To do this I focus on three sites of investigation. I first examine privacy tool Ghostery and the ways in which Ghostery users' negotiate their positions as data-tracked subjects, especially in relation to privacy, knowledge and their sense of self. I then investigate Facebook's autoposting apps as examples of algorithmic personalisation that act on the user's behalf, and draw on the accounts of Facebook app users to explore themes such as identity performance, autonomous control and algorithmic governance. Finally I examine users' engagement with the ‘predictive powers' (Google Now, 2014) of the personalisation app Google Now, specifically in regards to notions of user trust, expectation and speculation. My critical enquiries produced a number of themes that tie this thesis together. Central were: the epistemic uncertainties that emerged as trust and anxiety in participant responses; the implications for a performative understanding of selfhood when algorithmic personalisation intervenes in user self-articulation; the (asymmetrical) data-for-services exchange which web users must negotiate with commercial data trackers; and the struggle for autonomy between user and system that algorithmic personalisation creates. The thesis also argues that algorithmic personalisation demands that web users' identities be constituted as both a stable and fixable ‘single identity', but also as recursively reworkable, dividualised and endlessly expressable entities.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: TK5105.55 Computer network protocols. Standards. General works