Computational Network Science: An Algorithmic Approach

The emerging field of network science represents a new style of research that can unify such traditionally-diverse fields as sociology, economics, physics, biology, and computer science. It is a powerful tool in analyzing both natural and man-made systems, using the relationships between players within these networks and between the networks themselves to gain insight into the nature of each field. Until now, studies in network science have been focused on particular relationships that require varied and sometimes-incompatible datasets, which has kept it from being a truly universal discipline.

Computational Network Science seeks to unify the methods used to analyze these diverse fields. This book provides an introduction to the field of Network Science and provides the groundwork for a computational, algorithm-based approach to network and system analysis in a new and important way. This new approach would remove the need for tedious human-based analysis of different datasets and help researchers spend more time on the qualitative aspects of network science research.

• Demystifies media hype regarding Network Science and serves as a fast-paced introduction to state-of-the-art concepts and systems related to network science
• Comprehensive coverage of Network Science algorithms, methodologies, and common problems
• Includes references to formative and updated developments in the field
• Coverage spans mathematical sociology, economics, political science, and biological networks

Table of Contents

Part I: Preliminaries
Chapter 1. Overview: Network Models and Theories
Chapter 2. Social Network Analysis
Chapter 3. Network Games
Chapter 4. Economic Networks
Chapter 5. Political Networks
Chapter 6. Interactions
Chapter 7. Diffusion
Chapter 8. Social Influence
Chapter 9. Power

Part II: Groups
Chapter 10. Community Detection
Chapter 11. Collective Action

Part III: Advanced Research Topics
Chapter 12. Social Capital
Chapter 13. Organizations
Chapter 14. Emerging topics