Social-Behavioral Modeling for Complex Systems

This volume describes frontiers in social-behavioral modeling for contexts as diverse as national security, health, and on-line social gaming. Recent scientific and technological advances have created exciting opportunities for such improvements. However, the book also identifies crucial scientific, ethical, and cultural challenges to be met if social-behavioral modeling is to achieve its potential. Doing so will require new methods, data sources, and technology. The volume discusses these, including those needed to achieve and maintain high standards of ethics and privacy. The result should be a new generation of modeling that will advance science and, separately, aid decision-making on major social and security-related subjects despite the myriad uncertainties and complexities of social phenomena.

Intended to be relatively comprehensive in scope, the volume balances theory-driven, data-driven, and hybrid approaches. The latter may be rapidly iterative, as when artificial-intelligence methods are coupled with theory-driven insights to build models that are sound, comprehensible and usable in new situations.

With the intent of being a milestone document that sketches a research agenda for the next decade, the volume draws on the wisdom, ideas and suggestions of many noted researchers who draw in turn from anthropology, communications, complexity science, computer science, defense planning, economics, engineering, health systems, medicine, neuroscience, physics, political science, psychology, public policy and sociology.

In brief, the volume discusses:

• Cutting-edge challenges and opportunities in modeling for social and behavioral science

• Special requirements for achieving high standards of privacy and ethics

• New approaches for developing theory while exploiting both empirical and computational data

• Issues of reproducibility, communication, explanation, and validation

• Special requirements for models intended to inform decision making about complex social systems

Autorentext

Paul K. Davis, PhD, is a senior principal researcher at the RAND Corporation and a professor of policy analysis at the Pardee RAND Graduate School. Angela O'Mahony, PhD, is a senior political scientist at the RAND Corporation and a professor at the Pardee RAND Graduate School. Jonathan Pfautz, PhD, is a Program Manager at DARPA.

Inhalt
Foreword xxvii

List of Contributors xxxi

About the Editors xli

About the Companion Website xliii

Part I Introduction and Agenda 1

1 Understanding and Improving the Human Condition: A Vision of the Future for Social-Behavioral Modeling **3
**Jonathan Pfautz, Paul K. Davis, and Angela O'Mahony

Challenges 5

About This Book 10

References 13

2 Improving Social-Behavioral Modeling **15
**Paul K. Davis and Angela O'Mahony

Aspirations 15

Classes of Challenge 17

Inherent Challenges 17

Selected Specific Issues and the Need for Changed Practices 20

Strategy for Moving Ahead 32

Social-Behavioral Laboratories 39

Conclusions 41

Acknowledgments 42

References 42

**3 Ethical and Privacy Issues in Social-Behavioral Research 49
**Rebecca Balebako, Angela O'Mahony, Paul K. Davis, and Osonde Osoba

Improved Notice and Choice 50

Usable and Accurate Access Control 52

Anonymization 53

Avoiding Harms by Validating Algorithms and Auditing Use 55

Challenge and Redress 56

Deterrence of Abuse 57

And Finally Thinking Bigger About What Is Possible 58

References 59

Part II Foundations of Social-Behavioral Science 63

**4 Building on Social Science: Theoretic Foundations for Modelers 65
**Benjamin Nyblade, Angela O'Mahony, and Katharine Sieck

Background 65

Atomistic Theories of Individual Behavior 66

Social Theories of Individual Behavior 75

Theories of Interaction 80

From Theory to Data and Data to Models 88

Building Models Based on Social Scientific Theories 92

Acknowledgments 94

References 94

**5 How Big and How Certain? A New Approach to Defining Levels of Analysis for Modeling Social Science Topics 101
**Matthew E. Brashears

Introduction 101

Traditional Conceptions of Levels of Analysis 102

Incompleteness of Levels of Analysis 104

Constancy as the Missing Piece 107

Putting It Together 111

Implications for Modeling 113

Conclusions 116

Acknowledgments 116

References 116

**6 Toward Generative Narrative Models of the Course and Resolution of Conflict 121
**Steven R. Corman, Scott W. Ruston, and Hanghang Tong

Limitations of Current Conceptualizations of Narrative 122

A Generative Modeling Framework 125

Application to a Simple Narrative 126

Real-World Applications 130

Challenges and Future Research 133

Conclusion 135

Acknowledgment 137

Locations, Events, Actions, Participants, and Things in the Three Little Pigs 137

Edges in the Three Little Pigs Graph 139

References 142

**7 A Neural Network Model of Motivated Decision-Making in Everyday Social Behavior 145
**Stephen J. Read and Lynn C. Miller

Introduction 145

Overview 146

Theoretical Background 147

Neural Network Implementation 151

Conclusion 159

References 160

**8 Dealing with Culture as Inherited Information 163
**Luke J. Matthews

Galton's Problem as a Core Feature of Cultural Theory 163

How to Correct for Treelike Inheritance of Traits Across Groups 167

Dealing with Non independence in Less Treelike Network Structures 173

Future Directions for Formal Modeling of Culture 178

Acknowledgments 181

References 181 **9 Social Media, Global Connections, and Information Environments: Building Complex Understandings of Multi-Actor Interactions 187
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