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.

• Foreword xxviiList of Contributors xxxiAbout the Editors xliAbout the Companion Website xliiiPart I Introduction and Agenda 11 Understanding and Improving the Human Condition: A Vision of the Future for Social-Behavioral Modeling 3Jonathan Pfautz, Paul K. Davis, and Angela O’MahonyChallenges 5About This Book 10References 132 Improving Social-Behavioral Modeling 15Paul K. Davis and Angela O’MahonyAspirations 15Classes of Challenge 17Inherent Challenges 17Selected Specific Issues and the Need for Changed Practices 20Strategy for Moving Ahead 32Social-Behavioral Laboratories 39Conclusions 41Acknowledgments 42References 423 Ethical and Privacy Issues in Social-Behavioral Research 49Rebecca Balebako, Angela O’Mahony, Paul K. Davis, and Osonde OsobaImproved Notice and Choice 50Usable and Accurate Access Control 52Anonymization 53Avoiding Harms by Validating Algorithms and Auditing Use 55Challenge and Redress 56Deterrence of Abuse 57And Finally Thinking Bigger About What Is Possible 58References 59Part II Foundations of Social-Behavioral Science 634 Building on Social Science: Theoretic Foundations for Modelers 65Benjamin Nyblade, Angela O’Mahony, and Katharine SieckBackground 65Atomistic Theories of Individual Behavior 66Social Theories of Individual Behavior 75Theories of Interaction 80From Theory to Data and Data to Models 88Building Models Based on Social Scientific Theories 92Acknowledgments 94References 945 How Big and How Certain? A New Approach to Defining Levels of Analysis for Modeling Social Science Topics 101Matthew E. BrashearsIntroduction 101Traditional Conceptions of Levels of Analysis 102Incompleteness of Levels of Analysis 104Constancy as the Missing Piece 107Putting It Together 111Implications for Modeling 113Conclusions 116Acknowledgments 116References 1166 Toward Generative Narrative Models of the Course and Resolution of Conflict 121Steven R. Corman, Scott W. Ruston, and Hanghang TongLimitations of Current Conceptualizations of Narrative 122A Generative Modeling Framework 125Application to a Simple Narrative 126Real-World Applications 130Challenges and Future Research 133Conclusion 135Acknowledgment 137Locations, Events, Actions, Participants, and Things in the Three Little Pigs 137Edges in the Three Little Pigs Graph 139References 1427 A Neural Network Model of Motivated Decision-Making in Everyday Social Behavior 145Stephen J. Read and Lynn C. MillerIntroduction 145Overview 146Theoretical Background 147Neural Network Implementation 151Conclusion 159References 1608 Dealing with Culture as Inherited Information 163Luke J. MatthewsGalton’s Problem as a Core Feature of Cultural Theory 163How to Correct for Treelike Inheritance of Traits Across Groups 167Dealing with Non independence in Less Treelike Network Structures 173Future Directions for Formal Modeling of Culture 178Acknowledgments 181References 1819 Social Media, Global Connections, and Information Environments: Building Complex Understandings of Multi-Actor Interactions 187Gene Cowherd and Daniel LendeA New Setting of Hyperconnectivity 187The Information Environment 188Social Media in the Information Environment 189Integrative Approaches to Understanding Human Behavior 190The Ethnographic Examples 192Conclusion 202References 20410 Using Neuroimaging to Predict Behavior: An Overview with a Focus on the Moderating Role of Sociocultural Context 205Steven H. Tompson, Emily B. Falk, Danielle S. Bassett, and Jean M. VettelIntroduction 205The Brain-as-Predictor Approach 206Predicting Individual Behaviors 208Interpreting Associations Between Brain Activation and Behavior 210Predicting Aggregate Out-of-Sample Group Outcomes 211Predicting Social Interactions and Peer Influence 214Sociocultural Context 215Future Directions 219Conclusion 221References 22211 Social Models from Non-Human Systems 231Theodore P. PavlicEmergent Patterns in Groups of Behaviorally Flexible Individuals 232Model Systems for Understanding Group Competition 239Information Dynamics in Tightly Integrated Groups 246Conclusions 254Acknowledgments 255References 25512 Moving Social-Behavioral Modeling Forward: Insights from Social Scientists 263Matthew Brashears, Melvin Konner, Christian Madsbjerg, Laura McNamara, and Katharine SieckWhy Do People Do What They Do? 264Everything Old Is New Again 264Behavior Is Social, Not Just Complex 267What is at Stake? 270Sensemaking 272Final Thoughts 275References 276Part III Informing Models with Theory and Data 27913 Integrating Computational Modeling and Experiments: Toward a More Unified Theory of Social Influence 281Michael GabbayIntroduction 281Social Influence Research 283Opinion Network Modeling 284Integrated Empirical and Computational Investigation of Group Polarization 286Integrated Approach 299Conclusion 305Acknowledgments 307References 30814 Combining Data-Driven and Theory-Driven Models for Causality Analysis in Sociocultural Systems 311Amy Sliva, Scott Neal Reilly, David Blumstein, and Glenn PierceIntroduction 311Understanding Causality 312Ensembles of Causal Models 317Case Studies: Integrating Data-Driven and Theory-Driven Ensembles 321Conclusions 332References 33315 Theory-Interpretable, Data-Driven Agent-Based Modeling 337William RandThe Beauty and Challenge of Big Data 337A Proposed Unifying Principle for Big Data and Social Science 340Data-Driven Agent-Based Modeling 342Conclusion and the Vision 353Acknowledgments 354References 35516 Bringing the Real World into the Experimental Lab: Technology-Enabling Transformative Designs 359Lynn C. Miller, Liyuan Wang, David C. Jeong, and Traci K. GilligUnderstanding, Predicting, and Changing Behavior 359Social Domains of Interest 360The SOLVE Approach 365Experimental Designs for Real-World Simulations 368Creating Representative Designs for Virtual Games 371Applications in Three Domains of Interest 375Conclusions 376References 38017 Online Games for Studying Human Behavior 387Kiran Lakkaraju, Laura Epifanovskaya, Mallory Stites, Josh Letchford, Jason Reinhardt, and Jon WhetzelIntroduction 387Online Games and Massively Multiplayer Online Games for Research 388War Games and Data Gathering for Nuclear Deterrence Policy 390MMOG Data to Test International Relations Theory 393Analysis and Results 397Games as Experiments: The Future of Research 403Final Discussion 405Acknowledgments 405References 40518 Using Sociocultural Data from Online Gaming and Game Communities 407Sean Guarino, Leonard Eusebi, Bethany Bracken, and Michael JenkinsIntroduction 407Characterizing Social Behavior in Gaming 409Game-Based Data Sources 412Case Studies of SBE Research in Game Environments 422Conclusions and Future Recommendations 437Acknowledgments 438References 43819 An Artificial Intelligence/Machine Learning Perspective on Social Simulation: New Data and New Challenges 443Osonde Osoba and Paul K. DavisObjectives and Background 443Relevant Advances 443Data and Theory for Behavioral Modeling and Simulation 454Conclusion and Highlights 470Acknowledgments 472References 47220 Social Media Signal Processing 477Prasanna Giridhar and Tarek AbdelzaherSocial Media as a Signal Modality 477Interdisciplinary Foundations: Sensors, Information, and Optimal Estimation 479Event Detection and Demultiplexing on the Social Channel 481Conclusions 492Acknowledgment 492References 49221 Evaluation and Validation Approaches for Simulation of Social Behavior: Challenges and Opportunities 495Emily Saldanha, Leslie M. Blaha, Arun V. Sathanur, Nathan Hodas, Svitlana Volkova, and Mark GreavesOverview 495Simulation Validation 498Simulation Evaluation: Current Practices 499Measurements, Metrics, and Their Limitations 500Proposed Evaluation Approach 507Conclusions 515References 515Part IV Innovations in Modeling 52122 The Agent-Based Model Canvas: A Modeling Lingua Franca for Computational Social Science 523Ivan Garibay, Chathika Gunaratne, Niloofar Yousefi, and Steve ScheinertIntroduction 523The Language Gap 527The Agent-Based Model Canvas 530Conclusion 540References 54123 Representing Socio-Behavioral Understanding with Models 545Andreas Tolk and Christopher G. GlaznerIntroduction 545Philosophical Foundations 546The Way Forward 562Acknowledgment 563Disclaimer 563References 56424 Toward Self-Aware Models as Cognitive Adaptive Instruments for Social and Behavioral Modeling 569Levent YilmazIntroduction 569Perspective and Challenges 571A Generic Architecture for Models as Cognitive Autonomous Agents 575The Mediation Process 578Coherence-Driven Cognitive Model of Mediation 581Conclusions 584References 58525 Causal Modeling with Feedback Fuzzy Cognitive Maps 587Osonde Osoba and Bart KoskoIntroduction 587Overview of Fuzzy Cognitive Maps for Causal Modeling 588Combining Causal Knowledge: Averaging Edge Matrices 592Learning FCM Causal Edges 594FCM Example: Public Support for Insurgency and Terrorism 597US–China Relations: An FCM of Allison’s Thucydides Trap 603Conclusion 611References 61226 Simulation Analytics for Social and Behavioral Modeling 617Samarth Swarup, Achla Marathe, Madhav V. Marathe, and Christopher L. BarrettIntroduction 617What Are Behaviors? 619Simulation Analytics for Social and Behavioral Modeling 624Conclusion 628Acknowledgments 630References 63027 Using Agent-Based Models to Understand Health-Related Social Norms 633Gita Sukthankar and Rahmatollah BeheshtiIntroduction 633Related Work 634Lightweight Normative Architecture (LNA) 634Cognitive Social Learners (CSL) Architecture 635Smoking Model 639Agent-Based Model 641Data 645Experiments 646Conclusion 652Acknowledgments 652References 65228 Lessons from a Project on Agent-Based Modeling 655Mirsad Hadzikadic and Joseph WhitmeyerIntroduction 655ACSES 656Verification and Validation 661Self-Organization and Emergence 665Trust 668Summary 669References 67029 Modeling Social and Spatial Behavior in Built Environments: Current Methods and Future Directions 673Davide Schaumann and Mubbasir KapadiaIntroduction 673Simulating Human Behavior – A Review 675Modeling Social and Spatial Behavior with MAS 678Discussion and Future Directions 685Acknowledgments 687References 68730 Multi-Scale Resolution of Human Social Systems: A Synergistic Paradigm for Simulating Minds and Society 697Mark G. OrrIntroduction 697The Reciprocal Constraints Paradigm 699Discussion 706Acknowledgments 708References 70831 Multi-formalism Modeling of Complex Social-Behavioral Systems 711Marco Gribaudo, Mauro Iacono, and Alexander H. LevisPrologue 711Introduction 713On Multi-formalism 718Issues in Multi-formalism Modeling and Use 719Issues in Multi-formalism Modeling and Simulation 734Conclusions 736Epilogue 736References 73732 Social-Behavioral Simulation: Key Challenges 741Kathleen M. CarleyIntroduction 741Key Communication Challenges 742Key Scientific Challenges 743Toward a New Science of Validation 748Conclusion 749References 75033 Panel Discussion:Moving Social-Behavioral Modeling Forward 753Angela O’Mahony, Paul K. Davis, Scott Appling, Matthew E. Brashears, Erica Briscoe, Kathleen M. Carley, Joshua M. Epstein, Luke J. Matthews, Theodore P. Pavlic, William Rand, Scott Neal Reilly, William B. Rouse, Samarth Swarup, Andreas Tolk, Raffaele Vardavas, and Levent YilmazSimulation and Emergence 754Relating Models Across Levels 765Going Beyond Rational Actors 776References 784Part V Models for Decision-Makers 78934 Human-Centered Design of Model-Based Decision Support for Policy and Investment Decisions 791William B. RouseIntroduction 791Modeler as User 792Modeler as Advisor 792Modeler as Facilitator 793Modeler as Integrator 797Modeler as Explorer 799Validating Models 800Modeling Lessons Learned 801Observations on Problem-Solving 804Conclusions 806References 80735 A Complex Systems Approach for Understanding the Effect of Policy and Management Interventions on Health System Performance 809Jason Thompson, Rod McClure, and Andrea de SilvaIntroduction 809Understanding Health System Performance 811Method 813Model Narrative 815Policy Scenario Simulation 817Results 817Discussion 824Conclusions 826References 82736 Modeling Information and Gray Zone Operations 833Corey LofdahlIntroduction 833The Technological Transformation of War: Counterintuitive Consequences 835Modeling Information Operations: Representing Complexity 838Modeling Gray Zone Operations: Extending Analytic Capability 842Conclusion 845References 84737 Homo Narratus (The Storytelling Species): The Challenge (and Importance) of Modeling Narrative in Human Understanding 849Christopher PaulThe Challenge 849What Are Narratives? 850What Is Important About Narratives? 851What Can Commands Try to Accomplish with Narratives in Support of Operations? 856Moving Forward in Fighting Against, with, and Through Narrative in Support of Operations 857Conclusion: Seek Modeling and Simulation Improvements That Will Enable Training and Experience with Narrative 861References 86238 Aligning Behavior with Desired Outcomes: Lessons for Government Policy from the Marketing World 865Katharine SieckTechnique 1: Identify the Human Problem 867Technique 2: Rethinking Quantitative Data 869Technique 3: Rethinking Qualitative Research 876Summary 882References 88239 Future Social Science That Matters for Statecraft 885Kent C. MyersPerspective 885Recent Observations 885Interactions with the Intelligence Community 887Phronetic Social Science 888Cognitive Domain 891Reflexive Processes 893Conclusion 895References 89640 Lessons on Decision Aiding for Social-Behavioral Modeling 899Paul K. DavisStrategic Planning Is Not About Simply Predicting and Acting 899Characteristics Needed for Good Decision Aiding 901Implications for Social-Behavioral Modeling 918Acknowledgments 921References 923Index 927

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