Social-behavioral modeling for complex systems

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,...

Descripción completa

Detalles Bibliográficos
Otros Autores: Davis, Paul K., editor (editor), O'Mahony, Angela, editor, Pfautz, Jonathan, editor
Formato: Libro electrónico
Idioma:Inglés
Publicado: Hoboken, New Jersey : Wiley [2019]
Edición:First edition
Colección:THEi Wiley ebooks.
Materias:
Social psychology > Data processing.
Collective behavior.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630611506719
Tabla de Contenidos:
  • 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.

Ejemplares similares