Details

Autor(en) / Beteiligte

• Davis, Paul K.,
• O'Mahony, Angela,
• Pfautz, Jonathan,

Titel

Social-behavioral modeling for complex systems

Ist Teil von

• THEi Wiley ebooks.

Auflage

First edition

Ort / Verlag

Hoboken, New Jersey : Wiley,

Erscheinungsjahr

[2019]

Link zum Volltext

• Wiley Online Library - AutoHoldings Books

Beschreibungen/Notizen

• 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.
• 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
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• Description based on print version record.