Introduction to Computational Social Science: Principles and Applications

Description

This textbook provides a comprehensive and reader-friendly introduction to the field of computational social science (CSS). Presenting a unified treatment, the text examines in detail the four key methodological approaches of automated social information extraction, social network analysis, social complexity theory, and social simulation modeling. This updated new edition has been enhanced with numerous review questions and exercises to test what has been learned, deepen understanding through problem-solving, and to practice writing code to implement ideas. Topics and features: contains more than a thousand questions and exercises, together with a list of acronyms and a glossary; examines the similarities and differences between computers and social systems; presents a focus on automated information extraction; discusses the measurement, scientific laws, and generative theories of social complexity in CSS; reviews the methodology of social simulations, covering both variable- and object-oriented models. Preface to the Second Edition Preface to the First Edition Acknowledgements Contents Acronyms List of Figures List of Tables 1 Introduction 1.1 What Is Computational Social Science? 1.2 A Computational Paradigm of Society 1.3 CSS as an Instrument-Enabled Science 1.4 Examples of CSS Investigations: Pure Scientific Research Versus Applied Policy Analysis 1.5 Society as a Complex Adaptive System 1.5.1 What Is a CAS in CSS? 1.5.2 Tripartite Ontology of Natural, Human, and Artificial Systems 1.5.3 Simon's Theory of Artifacts: Explaining Basic Social Complexity 1.5.4 Civilization, Complexity, and Quality of Life: Role of Artificial Systems 1.6 Main Areas of CSS: An Overview 1.6.1 Automated Social Information Extraction 1.6.2 Social Networks 1.6.3 Social Complexity 1.6.4 Social Simulation Modeling 1.7 A Brief History of CSS 1.8 Main Learning Objectives Recommended Readings 2 Computation and Social Science 2.1 Introduction and Motivation 2.2 History and First Pioneers 2.3 Computers and Programs 2.3.1 Structure and Functioning of a Computer 2.3.2 Compilers and Interpreters 2.4 Computer Languages 2.5 Operators, Statements, and Control Flow 2.6 Coding Style 2.7 Abstraction, Representation, and Notation 2.8 Objects, Classes, and Dynamics in Unified Modeling Language (UML) 2.8.1 Ontology 2.8.2 The Unified Modeling Language (UML) 2.8.3 Attributes 2.8.4 Operations 2.9 Data Structures 2.10 Modules and Modularization 2.11 Computability and Complexity 2.12 Algorithms Exercises Recommended Readings 3 Automated Information Extraction 3.1 Introduction and Motivation 3.2 History and First Pioneers 3.3 Linguistics and Principles of Content Analysis: Semantics and Syntax 3.4 Semantic Dimensions of Meaning: From Osgood to Heise 3.4.1 EPA-Space and the Structure of Human Information Processing and Meaning 3.4.2 Cross-Cultural Universality of Meaning 3.5 Data Mining: Overview 3.6 Data Mining: Methodological Process 3.6.1 Research Questions 3.6.2 Source Data: Selection and Procurement 3.6.3 Preprocessing Preparations 3.6.4 Analysis 3.6.5 Communication Recommended Readings 4 Social Networks 4.1 Introduction and Motivation 4.2 History and First Pioneers 4.3 Definition of a Network 4.3.1 A Social Network as a Class Object 4.3.2 Relational Types of Social Networks 4.3.3 Level of Analysis 4.3.4 Dynamic Networks 4.4 Elementary Social Network Structures 4.5 The Network Matrix 4.6 Quantitative Measures of a Social Network 4.6.1 Nodal Measures: Micro Level 4.6.2 Network Measures: Macro-Level 4.7 Dynamic (Actually, Kinetic) Networks as Ternary Associations 4.8 Applications 4.8.1 Human Cognition and Belief Systems 4.8.2 Decision-Making Models 4.8.3 Organizations and Meta-Models 4.8.4 Supply Chains 4.8.5 The Social Structure of Small Worlds 4.8.6 International Relations 4.9 Software for SNA Exercises Recommended Readings 5 Social Complexity I: Origins and Measurement 5.1 Introduction and Motivation 5.2 History and First Pioneers 5.3 Origins and Evolution of Social Complexity 5.3.1 Sociogenesis: The ``Big Four'' Primary Polity Networks 5.3.2 Social Complexity Elsewhere: Secondary Polity Networks 5.3.3 Contemporary Social Complexity: Globalization 5.3.4 Future Social Complexity 5.4 Conceptual Foundations 5.4.1 What Is Social Complexity? 5.4.2 Defining Features of Social Complexity 5.5 Measurement of Social Complexity 5.5.1 Qualitative Indicators: Lines of Evidence 5.5.2 Quantitative Indicators Recommended Readings 6 Social Complexity II: Laws 6.1 Introduction and Motivation 6.2 History and First Pioneers 6.3 Laws of Social Complexity: Descriptions 6.3.1 Structural Laws: Serial, Parallel, and Hybrid Complexity 6.3.2 Distributional Laws: Scaling and Nonequilibrium Complexity 6.4 Power Law Analysis 6.4.1 Empirical Analysis: Estimation and Assessing Goodness of Fit 6.4.2 Theoretical Analysis: Deriving Implications 6.5 Universality in Laws of Social Complexity Recommended Readings 7 Social Complexity III: Theories 7.1 Introduction and Motivation 7.2 History and First Pioneers 7.3 Theories of Social Complexity: Elements of Explanation 7.3.1 Sequentiality: Modeling Processes. Forward Logic 7.3.2 Conditionality: Modeling Causes. Backward Logic 7.3.3 Hybrid Bimodal Social Complexity: Several-Among-Some Causes 7.4 Explaining Initial Social Complexity 7.4.1 Emergence of Chiefdoms 7.4.2 Emergence of States 7.5 General Theories of Social Complexity 7.5.1 Theory of Collective Action 7.5.2 Simon's Theory of Adaptation via Artifacts 7.5.3 Canonical Theory as a Unified Framework Recommended Readings 8 Simulations I: Methodology 8.1 Introduction and Motivation 8.2 History and First Pioneers 8.3 Purpose of Simulation: Investigating Social Complexity Via Virtual Worlds 8.4 Basic Simulation Terminology 8.5 Fidelity of Representation and Implications 8.6 Types of Social Simulation: From System Dynamics to Agent-Based Models 8.7 Development Methodology of Social Simulations 8.7.1 Motivation: What Are the Research Questions Addressed by a Given Model? 8.7.2 Conceptual Design: What Does the Abstraction Look Like? 8.7.3 Implementation: How Is the Abstracted Model Written in Code? 8.7.4 Verification: Does the Simulation Perform as Intended? 8.7.5 Validation: Can We Trust the Results? 8.7.6 Virtual Experiments and Scenario Analyses: What New Information Does the Simulation Generate? 8.8 Assessing the Quality of a Social Simulation 8.8.1 General Principles for Social Modeling Assessment 8.8.2 Dimensions of Quality in Social Simulation Models 8.9 Methodology of Complex Social Simulations 8.10 Comparing Simulations: How Are Computational Models Compared? Recommended Readings 9 Simulations II: Variable-Oriented Models 9.1 Introduction and Motivation 9.2 History and First Pioneers 9.3 System Dynamics Models 9.3.1 Motivation: Research Questions 9.3.2 Design: Abstracting Conceptual and Formal Models 9.3.3 Implementation: System Dynamics Software 9.3.4 Verification 9.3.5 Validation 9.3.6 Analysis 9.4 Queueing Models 9.4.1 Motivation: Research Questions 9.4.2 Design: Abstracting Conceptual and Formal Models 9.4.3 Implementation: Queuing Systems Software 9.4.4 Verification 9.4.5 Validation 9.4.6 Analysis Recommended Readings 10 Simulations III: Object-Oriented Models 10.1 Introduction and Motivation 10.2 History and First Pioneers 10.3 Cellular Automata Models 10.3.1 Motivation: Research Questions 10.3.2 Design: Abstracting Conceptual and Formal Models 10.3.3 Implementation: Cellular Automata Software 10.3.4 Verification 10.3.5 Validation 10.3.6 Analysis 10.4 Agent-Based Models 10.4.1 Motivation: Research Questions 10.4.2 Design: Abstracting Conceptual and Formal Models 10.4.3 Implementation: Agent-Based Simulation Systems 10.4.4 Verification 10.4.5 Validation 10.4.6 Analysis Recommended Readings Answers to Problems A.1 Chapter 1 A.2 Chapter 2 A.3 Chapter 3 A.4 Chapter 4 A.5 Chapter 5 A.6 Chapter 6 A.7 Chapter 7 A.8 Chapter 8 A.9 Chapter 9 A.10 Chapter 10 Glossary References Author Index Subject Index