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Discrimination and Privacy in the Information Society

Overview of attention for book
Cover of 'Discrimination and Privacy in the Information Society'

Table of Contents

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    Book Overview
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    Chapter 1 Data Dilemmas in the Information Society: Introduction and Overview
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    Chapter 2 What Is Data Mining and How Does It Work?
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    Chapter 3 Why Unbiased Computational Processes Can Lead to Discriminative Decision Procedures
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    Chapter 4 A Comparative Analysis of Anti-Discrimination and Data Protection Legislations
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    Chapter 5 The Discovery of Discrimination
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    Chapter 6 Discrimination Data Analysis: A Multi-disciplinary Bibliography
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    Chapter 7 Risks of Profiling and the Limits of Data Protection Law
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    Chapter 8 Explainable and Non-explainable Discrimination in Classification
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    Chapter 9 Knowledge-Based Policing: Augmenting Reality with Respect for Privacy
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    Chapter 10 Combining and Analyzing Judicial Databases
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    Chapter 11 Privacy-Preserving Data Mining Techniques: Survey and Challenges
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    Chapter 12 Techniques for Discrimination-Free Predictive Models
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    Chapter 13 Direct and Indirect Discrimination Prevention Methods
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    Chapter 14 Introducing Positive Discrimination in Predictive Models
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    Chapter 15 From Data Minimization to Data Minimummization
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    Chapter 16 Quality of Information, the Right to Oblivion and Digital Reputation
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    Chapter 17 Transparency in Data Mining: From Theory to Practice
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    Chapter 18 Data Mining as Search: Theoretical Insights and Policy Responses
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    Chapter 19 The Way Forward
Overall attention for this book and its chapters
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1 news outlet
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4 policy sources
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15 X users
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2 Facebook pages

Readers on

mendeley
81 Mendeley
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1 CiteULike
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Title
Discrimination and Privacy in the Information Society
Published by
Discrimination and Privacy in the Information Society, January 2013
DOI 10.1007/978-3-642-30487-3
ISBNs
978-3-64-230486-6, 978-3-64-230487-3, 978-3-64-244113-4
Authors

Custers, Bart Herman Maria

Editors

Bart Custers, Toon Calders, Bart Schermer, Tal Zarsky

X Demographics

X Demographics

The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
France 1 1%
Canada 1 1%
Unknown 78 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 20 25%
Student > Ph. D. Student 16 20%
Researcher 9 11%
Student > Bachelor 6 7%
Student > Doctoral Student 6 7%
Other 13 16%
Unknown 11 14%
Readers by discipline Count As %
Computer Science 24 30%
Social Sciences 22 27%
Engineering 4 5%
Arts and Humanities 3 4%
Business, Management and Accounting 3 4%
Other 14 17%
Unknown 11 14%