Uncertainty is an ever-present and ineradicable aspect of politics. It affects all important issues of governance and policy, in both domestic and international contexts. Rather than treating the uncertainty of politics as a mystery, this book provides an original and direct treatment of political uncertainty as a scientifically-knowable phenomenon with well-defined principles and substantive properties. Specific applications of this theory of political uncertainty are demonstrated in diverse areas of politics, examining such questions as when and how wars break out, when and how governments collapse, and when and how political cooperation emerges. The author shows how probability and mathematical modeling can play a central role in understanding such complex and fundamental issues.
This textbook provides a comprehensive and reader-friendly introduction to the field of computational social science (CSS). Presenting a unified treatment, the text examines in detail the four key methodological approaches of automated social information extraction, social network analysis, social complexity theory, and social simulation modeling. This updated new edition has been enhanced with numerous review questions and exercises to test what has been learned, deepen understanding through problem-solving, and to practice writing code to implement ideas. Topics and features: contains more than a thousand questions and exercises, together with a list of acronyms and a glossary; examines the similarities and differences between computers and social systems; presents a focus on automated information extraction; discusses the measurement, scientific laws, and generative theories of social complexity in CSS; reviews the methodology of social simulations, covering both variable- and object-oriented models.
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