Networks: An Introduction

This book brings together for the first time the most important breakthroughs in networks analysis from mathematics, physics, computer and information sciences, biology, and the social sciences, presenting them in a coherent fashion, and highlighting the strong interconnections between work in different areas. Subjects covered include the measurement and structure of networks in many branches of science, methods for analyzing network data, including methods developed in physics, statistics, and sociology, the fundamentals of graph theory, computer algorithms, and spectral methods, mathematical models of networks, including random graph models and generative models, and theories of dynamical processes taking place on networks.

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.

Review :
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. 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. Likely to become the standard introductory textbook for the study of networks. 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. 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.