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Cognitive Biases in Visualizations

Overview of attention for book
Cover of 'Cognitive Biases in Visualizations'

Table of Contents

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    Book Overview
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    Chapter 1 So, What Are Cognitive Biases?
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    Chapter 2 Studying Biases in Visualization Research: Framework and Methods
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    Chapter 3 Four Perspectives on Human Bias in Visual Analytics
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    Chapter 4 Bias by Default?
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    Chapter 5 Methods for Discovering Cognitive Biases in a Visual Analytics Environment
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    Chapter 6 Experts’ Familiarity Versus Optimality of Visualization Design : How Familiarity Affects Perceived and Objective Task Performance
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    Chapter 7 Data Visualization Literacy and Visualization Biases: Cases for Merging Parallel Threads
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    Chapter 8 The Biases of Thinking Fast and Thinking Slow
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    Chapter 9 Experimentally Evaluating Bias-Reducing Visual Analytics Techniques in Intelligence Analysis
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    Chapter 10 Promoting Representational Fluency for Cognitive Bias Mitigation in Information Visualization
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    Chapter 11 Designing Breadth-Oriented Data Exploration for Mitigating Cognitive Biases
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    Chapter 12 A Visualization Approach to Addressing Reviewer Bias in Holistic College Admissions
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    Chapter 13 Cognitive Biases in Visual Analytics—A Critical Reflection
Attention for Chapter 11: Designing Breadth-Oriented Data Exploration for Mitigating Cognitive Biases
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Citations

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Summary Dimensions citations
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Chapter title
Designing Breadth-Oriented Data Exploration for Mitigating Cognitive Biases
Chapter number 11
Book title
Cognitive Biases in Visualizations
Published by
Springer, Cham, January 2018
DOI 10.1007/978-3-319-95831-6_11
Book ISBNs
978-3-31-995830-9, 978-3-31-995831-6
Authors

Po-Ming Law, Rahul C. Basole

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 25%
Student > Ph. D. Student 3 19%
Unspecified 2 13%
Student > Doctoral Student 1 6%
Unknown 6 38%
Readers by discipline Count As %
Computer Science 5 31%
Unspecified 2 13%
Business, Management and Accounting 1 6%
Medicine and Dentistry 1 6%
Unknown 7 44%

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