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
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100 1 |a Deutschmann, Emanuel. 
245 1 0 |a Computational Conflict Research. 
250 |a 1st ed. 
264 1 |a Cham :  |b Springer International Publishing AG,  |c 2019. 
264 4 |c Ã2020. 
300 |a 1 online resource (270 pages) 
336 |a text  |b txt  |2 rdacontent 
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338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Computational Social Sciences Series 
505 0 |a 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. 
505 8 |a 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. 
505 8 |a 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. 
505 8 |a 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. 
588 |a Description based on publisher supplied metadata and other sources. 
590 |a Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2023. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.  
655 4 |a Electronic books. 
700 1 |a Lorenz, Jan. 
700 1 |a Nardin, Luis G. 
700 1 |a Natalini, Davide. 
700 1 |a Wilhelm, Adalbert F. X. 
776 0 8 |i Print version:  |a Deutschmann, Emanuel  |t Computational Conflict Research  |d Cham : Springer International Publishing AG,c2019  |z 9783030293321 
797 2 |a ProQuest (Firm) 
830 0 |a Computational Social Sciences Series 
856 4 0 |u https://ebookcentral.proquest.com/lib/matrademy/detail.action?docID=5975917  |z Click to View