Agent-Based Computational Sociology

Books

thumbnail image: Agent-Based Computational Sociology

Most of the intriguing social phenomena of our time, such as international terrorism, social inequality, and urban ethnic segregation, are consequences of complex forms of agent interaction that are difficult to observe methodically and experimentally. This book looks at a new research stream that makes use of advanced computer simulation modelling techniques to spotlight agent interaction that allows us to explain the emergence of social patterns. It presents a method to pursue analytical sociology investigations that look at relevant social mechanisms in various empirical situations, such as markets, urban cities, and organisations. 

This book:

  • Provides a comprehensive introduction to epistemological, theoretical and methodological features of agent-based modelling in sociology through various discussions and examples.
  • Presents the pros and cons of using agent-based models in sociology.
  • Explores agent-based models in combining quantitative and qualitative aspects, and micro- and macro levels of analysis.
  • Looks at how to pose an agent-based research question, identifying the model building blocks, and how to validate simulation results.
  • Features examples of agent-based models that look at crucial sociology issues.
  • Supported by an accompanying website featuring data sets and code for the models included in the book.

 

Agent-Based Computational Sociology is written in a common sociological language and features examples of models that look at all the traditional explanatory challenges of sociology. Researchers and graduate students involved in the field of agent-based modelling and computer simulation in areas such as social sciences, cognitive sciences and computer sciences will benefit from this book.

Preface ix

1 What is agent-based computational sociology all about? 1

1.1 Predecessors and fathers 3

1.2 The main ideas of agent-based computational sociology 9

1.2.1 The primacy of models 9

1.2.2 The generative approach 11

1.2.3 The micro–macro link 13

1.2.4 Process and change 15

1.2.5 The unexcluded middle 16

1.2.6 Trans-disciplinarity 17

1.3 What are ABMs? 18

1.4 A classification of ABM use in social research 20

References 26

2 Cooperation, coordination and social norms 33

2.1 Direct reciprocity and the persistence of interaction 36

2.2 Strong reciprocity and social sanctions 42

2.3 Disproportionate prior exposure 49

2.4 Partner selection 54

2.5 Reputation 62

2.6 The emergence of conventions 69

References 78

3 Social influence 85

3.1 Segregation dynamics 88

3.2 Threshold behavior and opinions 97

3.3 Culture dynamics and diversity 103

3.4 Social reflexivity 109

References 122

4 The methodology 131

4.1 The method 134

4.2 Replication 140

4.2.1 The querelle about segregation 144

4.2.2 The querelle about trust and mobility 147

4.3 Multi-level empirical validation 151

References 159

5 Conclusions 165

References 172

Appendix A 175

A.1 Research centers 175

A.2 Scientific associations 177

A.3 Journals 178

A.4 Simulation tools 179

References 179

Appendix B 181

B.1 Example I: Partner selection and dynamic networks (Boero, Bravo and Squazzoni 2010) 182

B.2 Example II: Reputation (Boero et al. 2010) 211

References 234

Index 235

Related Topics

Related Publications

Related Content

Address:

This website is provided by John Wiley & Sons Limited, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ (Company No: 00641132, VAT No: 376766987)

Published features on StatisticsViews.com are checked for statistical accuracy by a panel from the European Network for Business and Industrial Statistics (ENBIS)   to whom Wiley and StatisticsViews.com express their gratitude. This panel are: Ron Kenett, David Steinberg, Shirley Coleman, Irena Ograjenšek, Fabrizio Ruggeri, Rainer Göb, Philippe Castagliola, Xavier Tort-Martorell, Bart De Ketelaere, Antonio Pievatolo, Martina Vandebroek and Lance Mitchell.