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The Fitness of Information: Quantitative Assessments of Critical Evidence

ISBN: 978-1-118-59420-9
288 pages
July 2014
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Description

Theories and practices to assess critical information in a complex adaptive system

Organized for readers to follow along easily, The Fitness of Information: Quantitative Assessments of Critical Evidence provides a structured outline of the key challenges in assessing crucial information in a complex adaptive system. Illustrating a variety of computational and explanatory challenges, the book demonstrates principles and practical implications of exploring and assessing the fitness of information in an extensible framework of adaptive landscapes.

The book’s first three chapters introduce fundamental principles and practical examples in connection to the nature of aesthetics, mental models, and the subjectivity of evidence. In particular, the underlying question is how these issues can be addressed quantitatively, not only computationally but also explanatorily. The next chapter illustrates how one can reduce the level of complexity in understanding the structure and dynamics of scientific knowledge through the design and use of the CiteSpace system for visualizing and analyzing emerging trends in scientific literature. The following two chapters explain the concepts of structural variation and the fitness of information in a framework that builds on the idea of fitness landscape originally introduced to study population evolution. The final chapter presents a dual-map overlay technique and demonstrates how it supports a variety of analytic tasks for a new type of portfolio analysis.

The Fitness of Information: Quantitative Assessments of Critical Evidence also features:

  • In-depth case studies and examples that characterize far-reaching concepts, illustrate underlying principles, and demonstrate profound challenges and complexities at various levels of analytic reasoning
  • Wide-ranging topics that underline the common theme, from the subjectivity of evidence in criminal trials to detecting early signs of critical transitions and mechanisms behind radical patents
  • An extensible and unifying framework for visual analytics by transforming analytic reasoning tasks to the assessment of critical evidence

The Fitness of Information: Quantitative Assessments of Critical Evidence
is a suitable reference for researchers, analysts, and practitioners who are interested in analyzing evidence and making decisions with incomplete, uncertain, and even conflicting information. The book is also an excellent textbook for upper-undergraduate and graduate-level courses on visual analytics, information visualization, and business analytics and decision support systems.
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Table of Contents

Preface ix

1. Attention and Aesthetics 1

1.1. Attention, 1

1.1.1. What Is It That Attracts Our Attention? 2

1.1.2. Negative Information Attracts More Attention, 2

1.1.3. The Myths of Prehistoric Civilization, 5

1.2. Gestalt Principles, 6

1.2.1. Closure and Completeness, 6

1.2.2. Continuity and Smoothness, 8

1.2.3. Missing the Obvious, 9

1.3. Aesthetics, 11

1.3.1. The Golden Ratio, 11

1.3.2. Simplicity, 12

1.3.3. Regularity, 14

1.3.4. Beauty, 15

1.4. The Index of the Interesting, 17

1.4.1. Belief Updates, 18

1.4.2. Proteus Phenomenon, 18

1.4.3. Surprises, 19

1.4.4. Connecting the Dots, 23

1.5. Summary, 24

Bibliography, 25

2. Mental Models 27

2.1. Mental Models, 27

2.1.1. Pitfalls, 29

2.1.2. Communicating with Aliens, 31

2.1.3. Boundary Objects, 32

2.1.4. Wrong Models, 33

2.1.5. Competing Hypotheses, 41

2.2. Creativity, 47

2.2.1. Divergent Thinking, 49

2.2.2. Blind Variation and Selective Retention, 51

2.2.3. Binding Free-Floating Elements of Knowledge, 52

2.2.4. Janusian Thinking, 54

2.2.5. TRIZ, 57

2.2.6. Reasoning by Analogy, 59

2.2.7. Structural Holes, Brokerage, and Boundary Spanning, 59

2.3. Foresights, 61

2.3.1. Information Foraging, 61

2.3.2. Identifying Priorities, 63

2.3.3. Hindsight on Foresight, 65

2.4. Summary, 66

Bibliography, 67

3. Subjectivity of Evidence 71

3.1. The Value of Information, 71

3.2. Causes Célèbre, 74

3.2.1. The Sacco and Vanzetti Case, 74

3.2.2. The O.J. Simpson Case, 79

3.2.3. Ward Edwards’s Defense of Bayesian Thinking, 86

3.3. The Da Vinci Code, 87

3.3.1. Positive and Negative Reviews, 88

3.3.2. Decision Trees, 90

3.4. Supreme Court Opinions, 93

3.5. Apple versus Samsung, 100

3.6. Summary, 101

Bibliography, 101

4. Visualizing the Growth of Knowledge 103

4.1. Progressive Knowledge Domain Visualization, 105

4.1.1. The Structure of a Knowledge Domain, 106

4.1.2. Research Fronts and Intellectual Bases, 108

4.1.3. Strategies of Scientific Discoveries, 111

4.2. CiteSpace, 116

4.2.1. Design Rationale, 117

4.2.2. Basic Procedure, 119

4.2.3. Advanced Cocitation Analysis, 122

4.2.4. Toward a Tightly Connected Community, 128

4.3. Examples, 132

4.3.1. Terrorism Research, 132

4.3.2. Mass Extinctions, 136

4.3.3. Developing Expertise in Analytics and Topic Areas, 140

4.3.4. U.S. Supreme Court Landmark Cases, 142

4.4. Summary, 143

Bibliography, 143

5. Fitness Landscapes 147

5.1. Cognitive Maps, 147

5.1.1. The Legibility of Cognitive Maps, 147

5.1.2. Spatial Knowledge, 148

5.2. Fitness Landscapes, 149

5.2.1. Wright’s Adaptive Landscapes, 150

5.2.2. Fisher’s Geometric Model of Adaptation, 153

5.2.3. The Holey Landscape, 155

5.2.4. Kauffman’s NK Model, 156

5.2.5. Local Search and Adaptation, 157

5.2.6. Criticisms, 158

5.3. Applications of Fitness Landscapes, 159

5.3.1. Structure–Activity Relationship Landscapes, 159

5.3.2. Landscapes Beyond Evolutionary Biology, 161

5.4. Summary, 169

Bibliography, 170

6. Structural Variation 173

6.1. Complex Adaptive Systems, 173

6.1.1. Early Signs of Critical Transitions, 173

6.1.2. Early Signs of Great Ideas, 175

6.1.3. The Structural Variation Theory, 176

6.2. Radical Patents, 181

6.2.1. Patentability, 181

6.2.2. NK Models of Recombinant Patents, 182

6.2.3. Recombinant Search for High-Impact Radical Ideas, 184

6.2.4. Radical Inventions, 188

6.2.5. Genetically Evolved Patentable Ideas, 189

6.3. Bridging the Gaps, 192

6.3.1. The Principle of Boundary Spanning, 192

6.3.2. Baseline Networks, 193

6.3.3. Structural Variation Metrics, 195

6.3.4. Statistical Models, 198

6.4. Applications, 199

6.4.1. Small-World Networks, 200

6.4.2. Complex Network Analysis (1996–2004), 201

6.4.3. National Cancer Institute’s Patent Portfolio, 203

6.4.4. A Follow-Up Study, 211

6.5. Summary, 212

Bibliography, 212

7. Gap Analytics 217

7.1. Portfolio Analysis and Risk Assessment, 218

7.1.1. Portfolios of Grant Proposals, 219

7.2. Interactive Overlays, 225

7.2.1. Single-Map Overlays, 225

7.2.2. Dual-Map Overlays, 226

7.3. Examples of Dual-Map Overlays, 231

7.3.1. Portfolios of a Single Source, 231

7.3.2. Portfolios of Organizations, 234

7.3.3. Portfolios of Subject Matters, 239

7.3.4. Patterns in Trajectories, 243

7.4. Summary, 246

7.5. Conclusion, 247

Bibliography, 250

Index 253

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Author Information

CHAOMEI CHEN, PhD, is a Professor of Informatics in the College of Computing and Informatics at Drexel University. He is the creator of the widely used software CiteSpace, and author of several other books. Dr. Chen’s research expertise includes information visualization, visual analytics, quantitative studies of scientific literature, and theories of scientific discoveries.

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