TY - BOOK ID - 52541317 TI - Computational Conflict Research AU - Deutschmann, Emanuel AU - Deutschmann, Emanuel. AU - Lorenz, Jan. AU - Nardin, Luis G. AU - Natalini, Davide. AU - Wilhelm, Adalbert F. X. PY - 2020 SN - 3030293327 3030293335 PB - Cham Springer Nature DB - UniCat KW - Peace studies & conflict resolution KW - Society & social sciences KW - Terrorism, armed struggle KW - Data mining KW - Social sciences—Data processing. KW - Social sciences—Computer programs. KW - Peace. KW - Terrorism. KW - Political violence. KW - Data mining. KW - Computational Social Sciences. KW - Conflict Studies. KW - Terrorism and Political Violence. KW - Data Mining and Knowledge Discovery. KW - Algorithmic knowledge discovery KW - Factual data analysis KW - KDD (Information retrieval) KW - Knowledge discovery in data KW - Knowledge discovery in databases KW - Mining, Data KW - Database searching KW - Violence KW - Political crimes and offenses KW - Terrorism KW - Acts of terrorism KW - Attacks, Terrorist KW - Global terrorism KW - International terrorism KW - Political terrorism KW - Terror attacks KW - Terrorist acts KW - Terrorist attacks KW - World terrorism KW - Direct action KW - Insurgency KW - Subversive activities KW - Political violence KW - Terror KW - Coexistence, Peaceful KW - Peaceful coexistence KW - International relations KW - Disarmament KW - Peace-building KW - Security, International KW - Social sciences KW - Social sciences—Data processing KW - Social sciences—Computer programs KW - Peace UR - https://www.unicat.be/uniCat?func=search&query=sysid:52541317 AB - 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. ER -