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 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.
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Description of 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.
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Vendor
Publication
Publish Date
2020 Jun 22
ISBN
978-3-030-29333-8
About the authors
About I am a Senior Lecturer (Akademischer Rat) at the University of Göttingen's Institute of Sociology and an External Collaborator to the Global Mobilities Project at the European University Institute's Migration Policy Centre. I hold an MSc in Sociology from Oxford University and a PhD (with distinction) in the same field from BIGSSS. My research often cuts across disciplinary boundaries, covering survey research and network analyses on topics such as transnational mobility and migration, regional integration and globalization, power law structures and human behavior under uncertainty. I have been a visitor to Princeton University's Global Systemic Risk research community and the European Commission's Joint Research Centre.
Emanuel Deutschmann(editor)
I am an applied mathematician and social scientist who works on the modeling, analysis, and design of socio-economic systems. More about me I am particularly interested in the dynamics of opinion and attitude formation and how it influences democratic collective decision making through deliberative interaction. I see opinion dynamics as an interdisciplinary topic because it touches social psychology, game theory, and the dynamics of complex systems. It is on the one hand driven by automatic cognitive and emotional processes, on the other hand it has elements of a strategic game, especially in the run-up to poll, election or other collective decision. Finally, interaction in large groups can have surprising systemic effects on macroscopic outcomes going beyond the scope of the individual. I want to contribute to detecting such self-driven hidden dynamics to better understand phenomena as polarization, the evolution of plurality, social cohesion, consensus and extremism in opinion landscapes. I want to find democratic innovations to aggregate the wisdom of the crowd (if it exists) in collective decisions under circumstances of ongoing opinion dynamics and strategic behavior of many people. I studied at the University of Bremen, where I also finished my doctoral studies in 2007. I was a post-doc at ETH Zurich at the Chair of Systems Design until 2009 and a scientist, lab manager and lecturer in political and social sciences at the at University of Oldenburg. Now I am with Jacobs University Bremen and Bremen International Graduate School of Social Sciences. I worked on the cohesion radar.
Jan Lorenz(editor)
My research interests center around the use and development of Modeling and Simulation methods and tools in combination with Artificial Intelligence and Statistical Analysis for understanding the impacts of social and human behaviors on the emergent properties of complex adaptive systems. Agent-Based Modeling Multiagent Systems Artificial Intelligence Simulation Data Analytics Computational Social Science
Luis G. Nardin(editor)
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