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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
Sommario
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 Com
Info autore
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.
Riassunto
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
