Networks: An Introduction

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Product Description

The scientific study of networks, including computer networks, social networks, and biological networks, has received an enormous amount of interest in the last few years. The rise of the Internet and the wide availability of inexpensive computers have made it possible to gather and analyze network data on a large scale, and the development of a variety of new theoretical tools has allowed us to extract new knowledge from many different kinds of networks.

The study of networks is broadly interdisciplinary and important developments have occurred in many fields, including mathematics, physics, computer and information sciences, biology, and the social sciences. 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 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.

Networks: An Introduction Review

The study of networks received much interest in recent years. This book provides an easy to read introduction covering many important topics. Hence its primary audience is probably for undergraduate students however it can serve also as reference.

In particular I like that the book focuses on many recent methods, e.g., community structures or complex network models, without forgetting past concept that have been developed either in graph theory or come from interdisciplinary research for instance from studying social networks. Also, it discusses network algorithms because only by means of these methods you can study the introduced concepts and methods numerically.

Mathematicians interested in graph theory will probably not like this book because it is not written in a typical math-style. In addition, the topic of the book is on network theory which is not exactly graph theory but comprises wider concepts (theoretically and practically).

Besides mathematician, probably everyone will like it.

I want to remark that this book is not merely a collection of published papers, but it is written as a textbook. This why the individual parts fit well to each other.

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