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Postdigital Aesthetics

Overview of attention for book
Cover of 'Postdigital Aesthetics'

Table of Contents

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    Book Overview
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    Chapter 1 Thinking Postdigital Aesthetics: Art, Computation and Design
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    Chapter 2 What Is ‘Post-digital’?
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    Chapter 3 Genealogies of the New Aesthetic
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    Chapter 4 The Postdigital Constellation
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    Chapter 5 Communication Models, Aesthetics and Ontology of the Computational Age Revealed
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    Chapter 6 How to Be Theorized: A Tediously Academic1 Essay on the New Aesthetic
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    Chapter 7 A Hyperbolic and Catchy New Aesthetic
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    Chapter 8 The Genius and the Algorithm: Reflections on the New Aesthetic as a Computer’s Vision
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    Chapter 9 Selfiecity: Exploring Photography and Self-Fashioning in Social Media
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    Chapter 10 Judging Like a Machine
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    Chapter 11 Not Now? Feminism, Technology, Postdigital
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    Chapter 12 Postscript on the Post-digital and the Problem of Temporality
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    Chapter 13 Dark Patterns: Interface Design, Augmentation and Crisis
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    Chapter 14 Data Visualization and the Subject of Political Aesthetics
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    Chapter 15 School Will Never End: On Infantilization in Digital Environments — Amplifying Empowerment or Propagating Stupidity?
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    Chapter 16 The City and the City: London 2012 Visual (Un)Commons
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    Chapter 17 Going Beyond the Visible: New Aesthetic as an Aesthetic of Blindness?
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    Chapter 18 Glitch Sorting: Minecraft, Curation and the Postdigital
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    Chapter 19 Through Glass Darkly: On Google’s Gnostic Governance
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    Chapter 20 New Aesthetic in the Perspective of Social Photography
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    Chapter 21 Aesthetics of the Banal — ‘New Aesthetics’ in an Era of Diverted Digital Revolutions
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    Chapter 22 Networks NOW: Belated Too Early
Attention for Chapter 9: Selfiecity: Exploring Photography and Self-Fashioning in Social Media
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Chapter title
Selfiecity: Exploring Photography and Self-Fashioning in Social Media
Chapter number 9
Book title
Postdigital Aesthetics
Published by
Palgrave Macmillan UK, January 2015
DOI 10.1057/9781137437204_9
Book ISBNs
978-1-349-49378-4, 978-1-137-43720-4

Alise Tifentale, Lev Manovich


David M. Berry, Michael Dieter

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 116 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 <1%
Italy 1 <1%
Australia 1 <1%
Sweden 1 <1%
Slovenia 1 <1%
Argentina 1 <1%
Belgium 1 <1%
Unknown 109 94%

Demographic breakdown

Readers by professional status Count As %
Student > Master 22 19%
Student > Ph. D. Student 21 18%
Student > Bachelor 16 14%
Researcher 8 7%
Lecturer > Senior Lecturer 7 6%
Other 30 26%
Unknown 12 10%
Readers by discipline Count As %
Arts and Humanities 32 28%
Social Sciences 32 28%
Computer Science 11 9%
Psychology 9 8%
Design 5 4%
Other 13 11%
Unknown 14 12%