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oapen-20.500.12657-230602024-03-22T19:23:37Z Computational Conflict Research Deutschmann, Emanuel Lorenz, Jan Nardin, Luis G. Natalini, Davide Wilhelm, Adalbert F. X. Social sciences Social sciences—Data processing Social sciences—Computer programs Peace Terrorism Political violence Data mining thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GT Interdisciplinary studies::GTU Peace studies and conflict resolution thema EDItEUR::J Society and Social Sciences thema EDItEUR::J Society and Social Sciences::JP Politics and government::JPW Political activism / Political engagement::JPWL Terrorism, armed struggle thema EDItEUR::U Computing and Information Technology::UN Databases::UNF Data mining 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. 2020-03-18 13:36:15 2020-04-01T09:01:53Z 2020-04-01T09:01:53Z 2020 book 1007098 http://library.oapen.org/handle/20.500.12657/23060 eng Computational Social Sciences application/pdf n/a 1007098.pdf https://www.springer.com/9783030293338 Springer Nature 10.1007/978-3-030-29333-8 10.1007/978-3-030-29333-8 6c6992af-b843-4f46-859c-f6e9998e40d5 264 Cham open access
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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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