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Title: Computational consumption : social media and the construction of digital consumers
Author: Alaimo, Cristina
ISNI:       0000 0004 5361 5519
Awarding Body: London School of Economics and Political Science (University of London)
Current Institution: London School of Economics and Political Science (University of London)
Date of Award: 2014
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The abundance of social data and the constant development of new models of personalized suggestions are rewriting the way in which consumption is experienced. Not only are consumers now immersed in an information mediated context - decoupled from physical and socio-cultural constrains - but they also experience other consumers and themselves differently, embracing the prescriptions of a technological medium made by algorithmic suggestions and software instructions. A single case study of a social shopping platform in its start up phase has served as the empirical object of this thesis. The company investigated represents a typical case in the field of data driven consumption. The case has been conducted following the company’s infrastructure design and implementation for over a year. The analysis of the case has revealed the distinctive computational logic embedded in the platform system. The system uses the data produced by user selection as representation of consumer choice. On this account it structures social and individual consumption patterns and computes personalized suggestion. This study shows that technological information and software systems disassemble traditional practices of consumption and reassemble consumers in new and unseen ways. The research investigates technology’s role as a medium, by exposing and deconstructing the processes through which data aggregation and personalization mechanics reconfigure discovery, selection and experience of fashion. This thesis illustrates how consumption is now produced on the basis of social data structuration and how consumers are constructed out of data assemblages. Consumers select products they are suggested to like or expected to buy reacting to what social media platforms construct, compute, and fed back to them. Personalization allows consumers to see themselves as individual against the background of a computed sociality. Ultimately thus, the study discusses the impact of computational consumption as individuation process, considering its implications for consumer identity articulation and marketing practices.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: PN1990 Broadcasting