Computational Conflict Research.

Bibliographic Details
Main Author: Deutschmann, Emanuel.
Other Authors: Lorenz, Jan., Nardin, Luis G., Natalini, Davide., Wilhelm, Adalbert F. X.
Format: eBook
Language:English
Published: Cham : Springer International Publishing AG, 2019.
Edition:1st ed.
Series:Computational Social Sciences Series
Subjects:
Online Access:Click to View
Table of Contents:
  • Intro
  • Acknowledgements
  • Contents
  • Contributors
  • List of Figures
  • List of Tables
  • Advancing Conflict Research Through Computational Approaches
  • 1 Introduction
  • 2 The Rise of Computational Social Science
  • 3 Computational Approaches to Conflict Research
  • 4 The Contributions of This Book
  • References
  • Part I Data and Methods in Computational Conflict Research
  • Advances in Data on Conflict and Dissent
  • 1 Introduction: The Need for Data in Computational Social Science
  • 2 Conflict Research and the Impact of the Early Conflict Data
  • 3 Data and Progress in Conflict Research
  • 4 The Essential Interaction Between Theory and Data in Conflict Research
  • 5 Key Unresolved Problems in Data for Conflict Research
  • 6 Conclusion
  • A.1 Appendix: Key Contemporary Data Sources, Listed Alphabetically
  • References
  • Text as Data for Conflict Research: A Literature Survey
  • 1 Introduction
  • 2 Dictionary Approaches for Conflict Research
  • 3 Supervised Methods
  • 4 Topic Modeling as Unsupervised Method in Conflict Research
  • 5 Techniques of Cross-Validation
  • 6 Conclusion
  • Appendix
  • References
  • Interdependencies in Conflict Dynamics: Analyzing Endogenous Patterns in Conflict Event Data Using Relational Event Models
  • 1 Introduction
  • 2 Relational Events
  • 3 Relational Event Models
  • 4 Controlling for Endogenous Network Effects
  • 5 Empirical Examples of Alliance Formation and Social Influencing
  • 5.1 Military Alliance-Formation Dynamics
  • 5.2 Influencing Dynamics Among EU Parliamentary Chambers
  • 6 Discussion
  • References
  • Part II Computational Research on Non-violent Conflict
  • Migration Policy Framing in Political Discourse: Evidence from Canada and the USA
  • 1 Introduction
  • 2 Theory
  • 2.1 Party-Based Issue Ownership
  • 2.2 Policy Framing
  • 2.3 Inter-Party Contest over Migration Policy
  • 2.4 Hypotheses.
  • 3 Data and Methods
  • 3.1 Comparative Case Study Approach
  • 3.2 Dataset Subsetting: Dictionary Approach
  • 3.3 Structural Topic Modeling
  • 3.4 Labeling and Categorizing Topics
  • 4 Results
  • 4.1 Topics in the USA and Canada
  • 4.2 Topic Association by Ideological Block
  • 4.3 Topic Prevalence Across Time
  • 4.4 Migration Policy Framing: Word Use
  • 5 Conclusion
  • A.1 Appendix
  • References
  • The Role of Network Structure and Initial Group Norm Distributions in Norm Conflict
  • 1 Introduction
  • 2 Social Norms
  • 2.1 Normative Conflict
  • 2.2 Finding Consensus
  • 3 Network Structure and Group Norm Distributions
  • 3.1 Homophily and Heterophily
  • 3.2 Group Size
  • 3.3 Initial Group Norm Distributions
  • 4 Agent-Based Model
  • 4.1 Simulating Norm Conflict
  • 4.2 Generation of Network Structure
  • 4.3 Initialization of Group Norm Distributions
  • 4.4 Norm Updating Process
  • 4.5 Outcome Metrics
  • 5 Simulation Results
  • 5.1 Change in Majority Norm
  • 5.2 Change in Group Norm Difference
  • 5.3 Conflict Ties
  • 6 Discussion and Conclusion
  • 6.1 The Alignment of Norms and Group Membership
  • 6.2 Homophily Balances In-Group and Between-Group Conflict
  • 6.3 Strategies to Maintain Minority Norms
  • 6.4 Limitations and Future Directions
  • Appendix: Analytical Derivations for Norm Endorsement
  • References
  • On the Fate of Protests: Dynamics of Social Activation and Topic Selection Online and in the Streets
  • 1 Introduction
  • 2 Data
  • 2.1 Iran Protest in 2017/2018
  • 2.2 PEGIDA, Germany Since 2014 and Ongoing
  • 2.3 Stylized Data Facts
  • 3 Agent-Based Model
  • 3.1 Agents, Follower Network, Thresholds, and Concerns
  • 3.2 Agents' Activities
  • 3.3 Initial Conditions and Stopping Rules
  • 4 Simulation Experiment
  • 4.1 The Iran Case in the Model
  • 4.2 The Germany Case in the Model
  • 4.3 Comparison Between the Iran and Germany Model Simulations.
  • 4.4 Parameter Study
  • 5 Discussion
  • References
  • Part III Computational Research on Violent Conflict
  • Do Non-State Armed Groups Influence Each Other in Attack Timing and Frequency? Generating, Analyzing, and Comparing Empirical Data and Simulation
  • 1 Introduction
  • 2 Data and Case Settings
  • 3 Methods
  • 3.1 Analytical Estimation
  • 3.2 Generative Model and Simulation
  • 4 Results
  • 4.1 Analytical Estimation of Basal and Additive Rates
  • 4.2 Comparison of Inferred Networks to the Network of Actual Ties
  • 4.3 Generative Model Results and Correspondence to Analytical Findings
  • 5 Conclusion
  • References
  • On the Beaten Path: Violence Against Civilians and Simulated Conflict Along Road Networks
  • 1 Introduction
  • 2 Conflict and Violence Against Civilians
  • 3 A New Strategy for Causal Identification: Creating Synthetic Events on the "Beaten Path"
  • 4 Data and Case Selection
  • 5 Modeling and Results
  • 6 Conclusion
  • References
  • Analysis of Conflict Diffusion Over Continuous Space
  • 1 Introduction
  • 2 Related Work
  • 2.1 Empirical Studies on the Diffusion of Conflict
  • 2.2 Grid Models
  • 2.3 Continuous Space Models
  • 3 Data
  • 4 Analysis
  • 4.1 Test for Complete Spatial Randomness
  • 4.2 Continuous Space Model
  • 4.3 Gaussian Process
  • 5 Discussion and Future Work
  • References
  • Rebel Group Protection Rackets: Simulating the Effects of Economic Support on Civil War Violence
  • 1 Introduction
  • 2 Theoretical Underpinnings
  • 2.1 Rebel Group Extortion and Looting
  • 2.2 Enterprise Fleeing
  • 2.3 Enterprise Reporting
  • 2.4 Rebel Group Fighting and Expansion
  • 2.5 Rebel Group Cooperation
  • 2.6 Rebel Group Recruitment
  • 3 Rebel Group Protection Rackets Model
  • 3.1 Model Description
  • 3.1.1 Income Process
  • 3.1.2 Demand Process
  • 3.1.3 Expand Process
  • 3.2 Scenario and Initialization
  • 3.3 Implementation.
  • 4 Experiments
  • 4.1 Security Experiments
  • 4.1.1 Rebel Group Strength
  • 4.1.2 Enterprise Allocation
  • 4.2 Somalia Case Study
  • 4.2.1 Historical Background
  • 4.2.2 Data and Experimentation
  • 5 Conclusion and Discussion
  • References
  • Online Material
  • Chapter 2: Inventory of Conflict Data
  • Chapter 4: R-Package Relational Event Models
  • Chapter 5: Supplementary Material and Replication Files to Migration Framing in Political Discourse
  • Chapter 6: Agent-Based Simulation Model Simulating Normative Conflict
  • Chapter 7: Agent-Based Simulation Model ProtestFate
  • Chapter 8: Agent-Based Simulation Model Non-State Armed Groups' Attack Timing
  • Chapter 9: Replication Code to On the Beaten Path
  • Chapter 10: Replication Code to Analysis of Conflict Diffusion over Continuous Space
  • Chapter 11: Agent-Based Simulation Model Rebel Group Protection Rackets
  • Index.