Social-Behavioral Modeling for Complex Systems.

Cover -- Title Page -- Copyright -- Contents -- Foreword -- List of Contributors -- About the Editors -- About the Companion Website -- Part I Introduction and Agenda -- Chapter 1 Understanding and Improving the Human Condition: A Vision of the Future for Social‐Behavioral Modeling -- Challenges -- Challenge One: The Complexity of Human Issues -- Challenge Two: Fragmentation -- Empirical Observation -- Empirical Experiments -- Generative Simulation -- Unification -- Challenge Three: Representations -- Challenge Four: Applications of Social‐Behavioral Modeling -- About This Book -- Roadmap for the Book -- References -- Chapter 2 Improving Social‐Behavioral Modeling -- Aspirations -- Vignette 1 -- Vignette 2 -- Classes of Challenge -- Inherent Challenges -- Individual Cognition and Behavior -- Social Systems as Complex Adaptive Systems (CAS) -- The Dynamic and Storytelling Character of People and Social Systems -- Wicked Problems -- Selected Specific Issues and the Need for Changed Practices -- Background on Fragmentation of SB Theories -- The Nature of Theory -- Similarities and Differences -- Rebalancing the Portfolio of Models and Methods -- Confronting Uncertainty -- Combination, Synthesis, and Integration -- Families of Multiresolution, Multiperspective Models -- Composability -- Connecting Theory with Evidence -- Rethinking Model Validity -- The Five Dimensions of Model Validity -- Assessing a Model's Validity in a Context -- Some General Criteria for Validation -- Strategy for Moving Ahead -- Tightening the Theory-Modeling-Experimentation Research Cycle -- Improving Theory and Related Modeling -- Social‐Behavioral Laboratories -- Conclusions -- Acknowledgments -- References -- Chapter 3 Ethical and Privacy Issues in Social‐Behavioral Research -- Improved Notice and Choice -- Diagnosis -- Prescriptions -- Usable and Accurate Access Control.

Diagnosis -- Prescriptions -- Anonymization -- Diagnosis -- Prescriptions -- Avoiding Harms by Validating Algorithms and Auditing Use -- Diagnosis -- Prescriptions -- Challenge and Redress -- Diagnosis -- Prescriptions -- Deterrence of Abuse -- Diagnosis -- Prescriptions -- And Finally Thinking Bigger About What Is Possible -- References -- Part II Foundations of Social-Behavioral Science -- Chapter 4 Building on Social Science: Theoretic Foundations for Modelers -- Background -- Atomistic Theories of Individual Behavior -- The Belief-Desire Model -- Desires -- Beliefs -- Cognition -- Alternative Atomistic Theories of Individual Behavior -- Social Theories of Individual Behavior -- Norms -- Descriptive Norms -- Norms as Social Expectation -- Norms as Moral and Ethical Obligations -- The Relationship between Normative and Rationalist Explanations of Behavior -- Theories of Interaction -- From Individual Behavior to Social Interaction -- Social Dilemmas and Collective Decision‐Making with Common Interests -- Bargaining over Conflicting Interests -- Social Interaction and the Dynamics of Beliefs -- Social Interaction and the Dynamics of Identity and Culture -- From Theory to Data and Data to Models -- Building Models Based on Social Scientific Theories -- Acknowledgments -- References -- Chapter 5 How Big and How Certain? A New Approach to Defining Levels of Analysis for Modeling Social Science Topics -- Introduction -- Traditional Conceptions of Levels of Analysis -- Incompleteness of Levels of Analysis -- Constancy as the Missing Piece -- Putting It Together -- Implications for Modeling -- Conclusions -- Acknowledgments -- References -- Chapter 6 Toward Generative Narrative Models of the Course and Resolution of Conflict -- Limitations of Current Conceptualizations of Narrative -- A Generative Modeling Framework -- Application to a Simple Narrative.

Real‐World Applications -- Challenges and Future Research -- Analysis Challenges -- Scale Challenges -- Sensitivity Challenge -- Conclusion -- Acknowledgment -- Locations, Events, Actions, Participants, and Things in the Three Little Pigs -- Edges in the Three Little Pigs Graph -- References -- Chapter 7 A Neural Network Model of Motivated Decision‐Making in Everyday Social Behavior -- Introduction -- Overview -- Constraint Satisfaction Processing -- Theoretical Background -- Motivational Systems -- Situations -- Interoceptive or Bodily State -- Wanting -- Competition Among Motives -- Motivation Changes Dynamically -- Neural Network Implementation -- General Processing in the Network -- Conclusion -- References -- Chapter 8 Dealing with Culture as Inherited Information -- Galton's Problem as a Core Feature of Cultural Theory -- How to Correct for Treelike Inheritance of Traits Across Groups -- Early Attempts to Correct Galton's Problem -- More Recent Attempts to Correct Galton's Problem -- Example Applications -- Dealing with Nonindependence in Less Treelike Network Structures -- Determining Which Network Is Most Important for a Cultural Trait -- Correcting for Network Nonindependence When Testing Trait-Trait Correlations -- Example Applications -- Future Directions for Formal Modeling of Culture -- Improved Network Autoregression Implementations -- A Global Data Set of Expected Nonindependence to Solve Galton's Problem -- Better Collection of Behavioral Trait Variation Across Populations -- Acknowledgments -- References -- Chapter 9 Social Media, Global Connections, and Information Environments: Building Complex Understandings of Multi‐Actor Interactions -- A New Setting of Hyperconnectivity -- The Information Environment -- Social Media in the Information Environment -- Integrative Approaches to Understanding Human Behavior -- Muddy the Waters.

Missing It -- Wag the Dog -- The Ethnographic Examples -- Muddying the Waters: The Case of Cassandra -- Missing It: The Case of SSgt Michaels -- Wag the Dog: The Case of Fedor the Troll -- Conclusion -- References -- Chapter 10 Using Neuroimaging to Predict Behavior: An Overview with a Focus on the Moderating Role of Sociocultural Context -- Introduction -- The Brain‐as‐Predictor Approach -- Predicting Individual Behaviors -- Interpreting Associations Between Brain Activation and Behavior -- Predicting Aggregate Out‐of‐Sample Group Outcomes -- Predicting Social Interactions and Peer Influence -- Sociocultural Context -- Future Directions -- Conclusion -- References -- Chapter 11 Social Models from Non-Human Systems -- Emergent Patterns in Groups of Behaviorally Flexible Individuals -- From Bird Motivations to Human Applications -- Game‐Theoretic Model of Frequency‐Dependent Tactic Choice -- Mathematical Model as Behavioral Microscope on Carefully Prepared Birds -- Transferable Insights from Behavioral Games to Human Groups -- Model Systems for Understanding Group Competition -- Social Spiders as Model Systems for Understanding Personality in Groups -- Ants as Model Systems for Understanding the Costs and Benefits of Specialization -- Personality and Specialization: From Nonhuman to Human Groups -- Information Dynamics in Tightly Integrated Groups -- Linear and Nonlinear Recruitment Dynamics -- Herd Behavior and Information Cascades in Ants -- From Ants to Human Decision Support Systems -- Additional Examples: Rationality and Memory -- Conclusions -- Acknowledgments -- References -- Chapter 12 Moving Social‐Behavioral Modeling Forward: Insights from Social Scientists -- Why Do People Do What They Do? -- Everything Old Is New Again -- Behavior Is Social, Not Just Complex -- What is at Stake? -- Sensemaking -- Final Thoughts -- References.

Part III Informing Models with Theory and Data -- Chapter 13 Integrating Computational Modeling and Experiments: Toward a More Unified Theory of Social Influence -- Introduction -- Social Influence Research -- Opinion Network Modeling -- Integrated Empirical and Computational Investigation of Group Polarization -- Group Polarization Theory -- Frame‐Induced Polarization Theory -- Accept‐Shift‐Constrict Model of Opinion Dynamics -- Experiment and Results -- Integrated Approach -- Conclusion -- Acknowledgments -- References -- Chapter 14 Combining Data‐Driven and Theory‐Driven Models for Causality Analysis in Sociocultural Systems -- Introduction -- Understanding Causality -- Ensembles of Causal Models -- Case Studies: Integrating Data‐Driven and Theory‐Driven Ensembles -- Letting the Data Speak: Additive Noise Ensembles -- Choosing Data‐Driven Approaches Using Theory -- Parameterizing Theory‐Driven Models Using Data -- Theory and Data Dialogue -- Conclusions -- References -- Chapter 15 Theory‐Interpretable, Data‐Driven Agent‐Based Modeling -- The Beauty and Challenge of Big Data -- A Proposed Unifying Principle for Big Data and Social Science -- Data‐Driven Agent‐Based Modeling -- Parameter Optimization -- News Consumption -- Urgent Diffusion -- Rule Induction -- Commuting Patterns -- Social Media Activity -- Conclusion and the Vision -- Acknowledgments -- References -- Chapter 16 Bringing the Real World into the Experimental Lab: Technology‐Enabling Transformative Designs -- Understanding, Predicting, and Changing Behavior -- Social Domains of Interest -- Preventing Disease -- Harm Mitigation in Crises -- Terrorism Reduction and Lone Actors -- The SOLVE Approach -- Overview of SOLVE -- Shame Reduction as a Key Intervention -- Intelligent Agents in Games -- Generalizing Approach: Understanding and Changing Behavior Across Domains.

Experimental Designs for Real‐World Simulations.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.