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.

Introduction.- Computation and Social Science.- Automated Information Extraction.- Social Networks.- Social Complexity I: Origins and Measurement.- Social Complexity II: Laws.- Social Complexity III: Theories.- Simulations I: Methodology.- Simulations II: Variable-Oriented Models.- Simulations III: Object-Oriented Models.

This indispensable textbook/reference provides a comprehensive and reader-friendly introduction to the emerging 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 and expanded 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 and further explore the concepts.Topics and features:Contains more than a thousand problem questions and exercises, together with a list of acronyms and a glossary of termsPresents an introduction to the main areas, core concepts, and historical development of CSS, providing examples of a range of CSS investigationsExamines the key similarities and differences between computers and social systems, from an information-processing perspectivePresents a focus on automated information extraction, beginning with its roots in linguisticsIntroduces the fundamental elements of social network analysis, and computational approaches to analyzing social complexityDiscusses the measurement, scientific laws, and generative theories of social complexity in CSSReviews the methodology of social simulations, covering in detail both variable-oriented and object-oriented modelsThis unique, clearly-written textbook is essential reading for graduate and advanced undergraduate students planning on embarking on a course on computational social science, or wishing to refresh their knowledge of the fundamental aspects of this exciting field.Dr. Claudio Cioffi-Revilla is University Professor and Professor of Computational Social Science, founding and former Chair of the Department of Computational Social Science, and founding and current Director of the Center for Social Complexity at George Mason University, VA, USA.

“This book is organized in a rigorous manner: each chapter includes an introductory abstract, a short chronology of the main achievements related to the chapter’s topic, well-balanced formalized-intuitive knowledge content, a significant number of questions … and finally a list of future readings. … I think Claudio Cioffi-Revilla’s work hits its assumed target: to be an affordable textbook for students and, at the same time, a useful support manual for instructors interested in learning or teaching computational social science.” (Valentin V. Inceu, Computing Reviews, February, 2019)“This well-organized book provides a timely and comprehensive systematic introduction to CSS. The chapters are relatively independent. Therefore, readers may quickly grasp related information by reading chapters selectively. … this book is intended as a CSS textbook for graduate students … .” (Chenyi Hu, Computing Reviews, August 11, 2014) ​

Expanded new edition enhanced with exercises and problems (with solutions) Introduces the key concepts in computational social science, providing formal definitions and a glossary Describes the scope of each sub-field, covering topics on information extraction, social networks, complexity theory and social simulations Discusses such methodological tools as extracting entities from text, computing social network indices and building an agent-based model Includes supplementary material: sn.pub/extras