Computational Conflict Research
This open access book brings together a set of original studies that use cutting-edge computational methods to investigate conflict at various geographic scales and degrees of intensity and violence. Methodologically, this book covers a variety of computational approaches from text mining and machin...
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| Published in | Computational social sciences |
|---|---|
| Main Authors | , , , , |
| Format | eBook |
| Language | English |
| Published |
Cham
Springer Nature
2020
Springer International Publishing AG Springer |
| Edition | 1 |
| Series | Computational Social Sciences |
| Subjects | |
| Online Access | Get full text |
| ISBN | 3030293327 9783030293321 9783030293338 3030293335 |
| ISSN | 2509-9574 2509-9582 |
| DOI | 10.1007/978-3-030-29333-8 |
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| Abstract | This open access book brings together a set of original studies that use cutting-edge computational methods to investigate conflict at various geographic scales and degrees of intensity and violence. Methodologically, this book covers a variety of computational approaches from text mining and machine learning to agent-based modelling and social network analysis. Empirical cases range from migration policy framing in North America and street protests in Iran to violence against civilians in Congo and food riots world-wide. Supplementary materials in the book include a comprehensive list of the datasets on conflict and dissent, as well as resources to online repositories where the annotated code and data of individual chapters can be found and where (agent-based) models can be re-produced and altered. These materials are a valuable resource for those wishing to retrace and learn from the analyses described in this volume and adapt and apply them to their own research interests. By bringing together novel research through an international team of scholars from a range of disciplines, Computational Conflict Research pioneers and maps this emerging field. The book will appeal to students, scholars, and anyone interested in the prospects of using computational social sciences to advance our understanding of conflict dynamics. |
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| AbstractList | This open access book brings together a set of original studies that use cutting-edge computational methods to investigate conflict at various geographic scales and degrees of intensity and violence. Methodologically, this book covers a variety of computational approaches from text mining and machine learning to agent-based modelling and social network analysis. Empirical cases range from migration policy framing in North America and street protests in Iran to violence against civilians in Congo and food riots world-wide. Supplementary materials in the book include a comprehensive list of the datasets on conflict and dissent, as well as resources to online repositories where the annotated code and data of individual chapters can be found and where (agent-based) models can be re-produced and altered. These materials are a valuable resource for those wishing to retrace and learn from the analyses described in this volume and adapt and apply them to their own research interests. By bringing together novel research through an international team of scholars from a range of disciplines, Computational Conflict Research pioneers and maps this emerging field. The book will appeal to students, scholars, and anyone interested in the prospects of using computational social sciences to advance our understanding of conflict dynamics. This open access book brings together a set of original studies that use cutting-edge computational methods to investigate conflict at various geographic scales and degrees of intensity and violence. Methodologically, this book covers a variety of computational approaches from text mining and machine learning to agent-based modelling and social network analysis. Empirical cases range from migration policy framing in North America and street protests in Iran to violence against civilians in Congo and food riots world-wide. Supplementary materials in the book include a comprehensive list of the datasets on conflict and dissent, as well as resources to online repositories where the annotated code and data of individual chapters can be found and where (agent-based) models can be re-produced and altered. These materials are a valuable resource for those wishing to retrace and learn from the analyses described in this volume and adapt and apply them to their own research interests. By bringing together novel research through an international team of scholars from a range of disciplines, Computational Conflict Research pioneers and maps this emerging field. The book will appeal to students, scholars, and anyone interested in the prospects of using computational social sciences to advance our understanding of conflict dynamics. |
| Author | Wilhelm, Adalbert F. X Deutschmann, Emanuel Lorenz, Jan Natalini, Davide Nardin, Luis G |
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| Editor | Wilhelm, Adalbert F. X Deutschmann, Emanuel Lorenz, Jan Natalini, Davide Nardin, Luis G |
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| PublicationSeriesTitle | Computational Social Sciences |
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| Snippet | This open access book brings together a set of original studies that use cutting-edge computational methods to investigate conflict at various geographic... |
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| SubjectTerms | Computing and Information Technology Data mining Interdisciplinary studies Military Nonfiction Peace Peace studies and conflict resolution Political activism / Political engagement Political violence Politics and government Reference, Information and Interdisciplinary subjects Social conflict Social sciences Social sciences—Computer programs Social sciences—Data processing Society and Social Sciences Sociology Terrorism Terrorism, armed struggle Violence |
| SubjectTermsDisplay | Electronic books. Military. Nonfiction. Reference. Sociology. |
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| TableOfContents | 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 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 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 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 |
| Title | Computational Conflict Research |
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