The emerging field of computational social science (CSS) is devoted to the pursuit of interdisciplinary social science research from an information processing perspective, through the medium of advanced computing and information technologies.

This reader-friendly textbook/reference is the first work of its kind to provide a comprehensive and unified Introduction to Computational Social Science. Four distinct methodological approaches are examined in particular detail, namely automated social information extraction, social network analysis, social complexity theory, and social simulation modeling. The coverage of each of these approaches is supported by a discussion of the historical context and motivations, as well as by a list of recommended texts for further reading.

Topics and features:

• Describes the scope and content of each area of CSS, covering topics on information extraction, social networks, complexity theory, and social simulations
• Highlights the main theories of the CSS paradigm as causal explanatory frameworks that shed new light on the nature of human and social dynamics
• Explains how to distinguish and analyze the different levels of analysis of social complexity using computational approaches
• Discusses a number of methodological tools, including extracting entities from text, computing social network indices, and building an agent-based model
• Presents the main classes of entities, objects, and relations common to the computational analysis of social complexity
• Examines the interdisciplinary integration of knowledge in the context of social phenomena

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 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 reader-friendly textbook is the first work of its kind to provide a unified Introduction to Computational Social Science (CSS). Four distinct methodological approaches are examined in detail, namely automated social information extraction, social network analysis, social complexity theory and social simulation modeling. The coverage of these approaches is supported by a discussion of the historical context, as well as by a list of texts for further reading. Features: highlights the main theories of the CSS paradigm as causal explanatory frameworks that shed new light on the nature of human and social dynamics; explains how to distinguish and analyze the different levels of analysis of social complexity using computational approaches; discusses a number of methodological tools; presents the main classes of entities, objects and relations common to the computational analysis of social complexity; examines the interdisciplinary integration of knowledge in the context of social phenomena.

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