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Agent-Based Modeling of Social Conflict : From Mechanisms to Complex Behavior.

Author: Carlos M Lemos
Publisher: Cham : Springer International Publishing, 2017.
Series: SpringerBriefs in complexity.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
This Brief revisits and extends Epstein's classical agent-based model of civil violence by considering important mechanisms suggested by social conflict theories. Among them are: relative deprivation as generator of hardship, generalized vanishing of the risk perception ('massive fear loss') when the uprisings surpass a certain threshold, endogenous legitimacy feedback, and network influence effects represented by  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Lemos, Carlos M.
Agent-Based Modeling of Social Conflict : From Mechanisms to Complex Behavior.
Cham : Springer International Publishing, ©2017
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Carlos M Lemos
ISBN: 9783319670508 3319670506 3319670492 9783319670492
OCLC Number: 1009309391
Notes: ""6.4.1 Relative Deprivation with Legitimacy Feedback""
Description: 1 online resource (132 pages)
Contents: Preface --
Acknowledgments --
Contents --
List of Symbols and Acronyms --
1 Introduction --
1.1 Purpose and Scope --
1.2 Objectives and Research Questions --
1.3 Methodology of Development and Structure of the Work --
2 Theoretical Foundations --
2.1 Overview of Social Conflict Theories --
2.2 Violence --
2.3 Ted Gurr's Frustration-Aggression Theory on the Psychological Factors of Civil Violence --
2.4 Gene Sharp's Theory of Non-Violent Action --
2.5 Legitimacy --
2.6 Concluding Remarks --
3 Review of Agent-Based Models of Social Conflict and Civil Violence 3.1 Agent Definition, Agent Types and Rule-Based Models of Binary Decision3.2 Epstein's Agent-Based Model of Civil Violence --
3.3 Discussion of Epstein's Agent-Based Model --
3.3.1 Scope --
3.3.2 Measures of Size, Duration, and Interval (Waiting Time) of Outbursts --
3.3.3 Input Parameters, Scales and Mechanisms --
3.4 Other Models Based Epstein's Agent-Based Model --
3.5 Concluding Remarks --
4 Analysis of Conflict Datasets and Indicators: The Case of the ``Arab Spring'' 4.1 Analysis of the Social Conflict Analysis Database for the African ``Arab Spring'' Countries4.1.1 A Note on Geographic Information, Accuracy of the Information, and Exceptional Events --
4.1.2 Question 1: How Important Were Demonstrations and Riots, in Terms of Number of Events and Estimated Number of Participants? --
4.1.3 Question 2: Which Were the Issues, Organization, and Escalation in Large Demonstrations and Riots? --
4.1.4 Question 3: What Were the Patterns of Recurrence, Duration and Size of Demonstrations and Riots? 4.2 Analysis of Fragile States Index Indicators for the African ``Arab Spring'' Countries4.3 Analysis of the Freedom in the World Indicator for the African ``Arab Spring'' Countries --
4.4 Analysis of the ``All the Ginis'' Dataset for the African ``Arab Spring'' Countries --
4.5 Concluding Remarks --
5 ABM of Civil Violence: ODD Description --
5.1 Purpose --
5.2 Entities, State Variables, and Scales --
5.2.1 Agents --
5.2.2 Networks --
5.2.3 Environment --
5.3 Process Overview and Scheduling --
5.4 Design Concepts --
5.4.1 Basic Principles --
5.4.2 Emergence 5.4.3 Adaptation5.4.4 Objectives --
5.4.5 Learning --
5.4.6 Prediction --
5.4.7 Sensing --
5.4.8 Interaction --
5.4.9 Stochasticity --
5.4.10 Collectives --
5.4.11 Observation --
5.4.12 Initialization --
5.4.13 Input Data --
5.4.14 Submodels --
5.5 R Scripts for Pre- and Post-Processing --
6 Model Exploration and Computer Experiments --
6.1 Risk Perception and the Estimated Arrest Probability --
6.1.1 Analytical Study --
6.1.2 Computer Experiments --
6.2 The Influence of the Jail Term --
6.3 Relative Deprivation --
6.4 Legitimacy Feedback
Series Title: SpringerBriefs in complexity.

Abstract:

This Brief revisits and extends Epstein's classical agent-based model of civil violence by considering important mechanisms suggested by social conflict theories. Among them are: relative deprivation as generator of hardship, generalized vanishing of the risk perception ('massive fear loss') when the uprisings surpass a certain threshold, endogenous legitimacy feedback, and network influence effects represented by the mechanism of dispositional contagion. The model is explored in a set of computer experiments designed to provide insight on how mechanisms lead to increased complexity of the solutions. The results of the simulations are compared with statistical analyses of estimated size, duration and recurrence of large demonstrations and riots for eight African countries affected by the "Arab Spring," based on the Social Conflict Analysis Database. It is shown that the extensions to Epstein's model proposed herein lead to increased "generative capacity" of the agent-based model (i.e. a richer set of meaningful qualitative behaviors) as well the identification of key mechanisms and associated parameters with tipping points. The use of quantitative information (international indicators and statistical analyses of conflict events) allows the assessment of the plausibility of input parameter values and simulated results, and thus a better understanding of the model's strengths and limitations. The contributions of the present work for understanding how mechanisms of large scale conflict lead to complexbehavior include a new form of the estimated arrest probability, a simple representation of political vs economic deprivation with a parameter which controls the sensitivity' to value, endogenous legitimacy feedback, and the effect of network influences (due to small groups and "activists"). In addition, the analysis of the Social Conflict Analysis Database provided a quantitative description of the impact of the "Arab Spring" in several countries focused on complexity issues such as peaceful vs violent, spontaneous vs organized, and patterns of size, duration and recurrence of conflict events in this recent and important large-scale conflict process. This book will appeal to students and researchers working in these computational social science subfields.

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