Table of Contents

1: Introduction
2: Technological Networks
3: Social Networks
4: Information Networks
5: Biological Networks
6: Mathematics of Networks
7: Measures and Metrics
8: The Large-scale Structure of Networks
9: Basic Concepts of Algorithms
10: Fundamental Network Algorithms
11: Matrix Algorithms and Graph Partitioning
12: Random Graphs
13: Generalized Random Graphs
14: Models of Network Formation
15: Other Network Models
16: Percolation and Network Resilience
17: Epidemics on Networks
18: Dynamical Systems on Networks
19: Network Search
References
Index

About the Author

Mark Newman received a D.Phil. in physics from the University of Oxford in 1991 and conducted postdoctoral research at Cornell University before joining the staff of the Santa Fe Institute, a think-tank in New Mexico devoted to the study of complex systems. In 2002 he left Santa Fe for the University of Michigan, where he is currently Paul Dirac Collegiate Professor of Physics and a professor in the university's Center for the Study of Complex Systems.

Reviews

Networks accomplishes two key goals: It provides a comprehensive introduction and presents the theoretic backbone of network science. [] The book is balanced in its presentation of theoretical concepts, computational techniques, and algorithms. The level of difficulty increases which each chapter [which] makes the book particularly valuable to physics students who wish to acquire a solid foundation based on their knowledge of basic linear algebra, calculus, and differential equations.
*Physics Today, 2011*

Newman has written a wonderful book that gives an extensive overview of the broadly interdisciplinary network-related developments that have occured in many fields, including mathematics, physics, computer science, biology, and the social sciences ... Overall, a valuable resource covering a wide-randing field.
*Choice*

Likely to become the standard introductory textbook for the study of networks.
*Computing Reviews*

Overall, this is an excellent textbook for the growing field of networks. It is cleverly written and suitable as both an introduction for undergraduate students (particularly Parts 1 to 3) and as a roadmap for graduate students. [] Being highly self-contained, computer scientists and professionals from other fields can also use the book—in fact, the author himself is a physicist. In short, this book is a delight for the inquisitive mind.
*Computing Reviews*

This book brings together, for the first time, the most important breakthroughs in each of these fields and presents them in a coherent fashion, highlighting the strong connections between work in different subject areas.
*Cern Courier*