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From Mass Culture to Personalization.

Weinberg, Lindsay A.

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From Mass Culture to Personalization.

Record Type:	Electronic resources : Monograph/item
Title/Author:	From Mass Culture to Personalization./
Author:	Weinberg, Lindsay A.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:	315 p.
Notes:	Source: Dissertation Abstracts International, Volume: 79-12(E), Section: A.
Contained By:	Dissertation Abstracts International79-12A(E).
Subject:	Communication. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10825330
ISBN:	9780438248809

From Mass Culture to Personalization.
Weinberg, Lindsay A.

From Mass Culture to Personalization. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 315 p.

Source: Dissertation Abstracts International, Volume: 79-12(E), Section: A.

Thesis (Ph.D.)--University of California, Santa Cruz, 2018.

This dissertation argues that personalization---the web of technologies and cultural practices that generate information about consumers to market goods and services to target audiences---is part of a larger cultural and economic transformation under digital capitalism. Building on the Frankfurt School's analysis of the mass culture industry, I use immanent critique to highlight the contradictions embedded in the celebratory rhetoric of digital media: its promises of customized, tailored, and interactive content, in contrast to the homogeneity and standardization of mass culture. I draw from Gilles Deleuze's "Postscript on Societies of Control" to argue that personalization technologies are actually predicated on "dividuation," the mass collection of data where individual subjects are fragmented into demographic data, preferences, and search habits for predicting future consumer behavior. Through discourse analysis, the study of laws regulating data, the critique of the political economy of personalization, and the study of its popular reception, I demonstrate how personalization aggregates consumer data to assess risk on capitalist investment, reproducing class, race, and gender biases in the distribution of market choices. In contrast to audience theories of labor, originally popularized by Dallas Smythe, this dissertation instead considers user attention to be part of a logistically coordinated digital economy where personalization is laborsaving to the extent that it cuts down on labor and supply costs. By providing an historical account of the rise of personalization as a technology of leisure-time surveillance emerging out of the 19th century revolution in bureaucratic modes of control, I show how capitalism uses media technologies to capture user attention for managing circulation. My analysis of marketing discourse and popular culture illustrates how personalization relies on gendered, racialized visions of technological subservience to conceal its operation as a technique of capital accumulation. Ultimately, this project provides a political framework for redressing the exploitation, unequal distribution of market choices, and pervasive surveillance that personalization entails through a critique of privacy rights discourse in the U.S. and E.U. I build on feminist approaches to political philosophy to argue that the non-sovereignty of the subject under commercial surveillance---dividuation---could also provide the basis for the socialized redistribution of big data profits.

ISBN: 9780438248809Subjects--Topical Terms:

524709
Communication.

From Mass Culture to Personalization.
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500 $a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: A.
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502 $a Thesis (Ph.D.)--University of California, Santa Cruz, 2018.
520 $a This dissertation argues that personalization---the web of technologies and cultural practices that generate information about consumers to market goods and services to target audiences---is part of a larger cultural and economic transformation under digital capitalism. Building on the Frankfurt School's analysis of the mass culture industry, I use immanent critique to highlight the contradictions embedded in the celebratory rhetoric of digital media: its promises of customized, tailored, and interactive content, in contrast to the homogeneity and standardization of mass culture. I draw from Gilles Deleuze's "Postscript on Societies of Control" to argue that personalization technologies are actually predicated on "dividuation," the mass collection of data where individual subjects are fragmented into demographic data, preferences, and search habits for predicting future consumer behavior. Through discourse analysis, the study of laws regulating data, the critique of the political economy of personalization, and the study of its popular reception, I demonstrate how personalization aggregates consumer data to assess risk on capitalist investment, reproducing class, race, and gender biases in the distribution of market choices. In contrast to audience theories of labor, originally popularized by Dallas Smythe, this dissertation instead considers user attention to be part of a logistically coordinated digital economy where personalization is laborsaving to the extent that it cuts down on labor and supply costs. By providing an historical account of the rise of personalization as a technology of leisure-time surveillance emerging out of the 19th century revolution in bureaucratic modes of control, I show how capitalism uses media technologies to capture user attention for managing circulation. My analysis of marketing discourse and popular culture illustrates how personalization relies on gendered, racialized visions of technological subservience to conceal its operation as a technique of capital accumulation. Ultimately, this project provides a political framework for redressing the exploitation, unequal distribution of market choices, and pervasive surveillance that personalization entails through a critique of privacy rights discourse in the U.S. and E.U. I build on feminist approaches to political philosophy to argue that the non-sovereignty of the subject under commercial surveillance---dividuation---could also provide the basis for the socialized redistribution of big data profits.
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