Introduction to Computational Social Science

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 terms
• Presents an introduction to the main areas, core concepts, and historical development of CSS, providing examples of a range of CSS investigations
• Examines the key similarities and differences between computers and social systems, from an information-processing perspective
• Presents a focus on automated information extraction, beginning with its roots in linguistics
• Introduces the fundamental elements of social network analysis, and computational approaches to analyzing social complexity
• Discusses the measurement, scientific laws, and generative theories of social complexity in CSS
• Reviews the methodology of social simulations, covering in detail both variable-oriented and object-oriented models

This 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.