Social-behavioral modeling for complex systems / edited by Paul K. Davis, Angela O'Mahony and Jonathan Pfautz.

Format:

Book

Contributor:

Davis, Paul K., editor.

O'Mahony, Angela, editor.

Pfautz, Jonathan, editor.

Series:

THEi Wiley ebooks.

Language:

English

Subjects (All):

Social psychology--Data processing.

Social psychology.

Collective behavior.

Physical Description:

1 online resource (947 pages)

Edition:

First edition

Place of Publication:

Hoboken, New Jersey : Wiley, [2019]

System Details:

Access using campus network via VPN at home (THEi Users Only).

text file

Summary:

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

Contents:

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

Chapter 3 Ethical and Privacy Issues in Social‐Behavioral Research

Improved Notice and Choice

Diagnosis

Prescriptions

Usable and Accurate Access Control.

Diagnosis

Anonymization

Avoiding Harms by Validating Algorithms and Auditing Use

Challenge and Redress

Deterrence of Abuse

And Finally Thinking Bigger About What Is Possible

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

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

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

Chapter 7 A Neural Network Model of Motivated Decision‐Making in Everyday Social Behavior

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

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

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

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

Chapter 10 Using Neuroimaging to Predict Behavior: An Overview with a Focus on the Moderating Role of Sociocultural Context

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

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

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

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

Chapter 14 Combining Data‐Driven and Theory‐Driven Models for Causality Analysis in Sociocultural Systems

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

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

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.

Notes:

Description based on print version record.

ISBN:

9781119484974

1119484979

9781119485001

1119485002

9781119484981

1119484987

OCLC:

1056201930