Networks

by M.E.J. Newman, Mark Newman

The study of networks, including computer networks, social networks, and biological networks, has attracted enormous 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 an unprecedented scale, and the development of new theoretical tools has allowed us to extract knowledge from networks of many different kinds. The study of networks is broadly interdisciplinary and central developments have occurred in many fields, including mathematics, physics, computer and information sciences, biology, and the social sciences. This book brings together 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.

Topics covered include the measurement of networks; methods for analyzing network data, including methods developed in physics, statistics, and sociology; fundamentals of graph theory; computer algorithms; mathematical models of networks, including random graph models and generative models; and theories of dynamical processes taking place on networks.

Genres: Science, Mathematics, Nonfiction, Computer Science, Textbooks, Biology, Engineering

800 pages, Hardcover

First published March 25, 2010

Reviews

[Joshua]

Whenever I hear biologists talking about something mathematical that I don't understand, I get worried. These days it is networks and "network theory". So I decided to read this book--it's great. Now I realize that all the biologists are talking about is a restricted form of graph theory, which is easily mapped (for me at least) into linear algebra. I would feel comfortable handing this to an undergraduate who was not afraid of a little math, as it is well presented and self-contained. Not sure if it is really useful for chemistry....but I was excited enough to think about that for a few days and cook up a few hare-brained research projects...

[Jonathan · Rating 4 out of 5]

Good text, but not compellingly written enough to slog through its entirety. Used mainly about 3 chapters, and parts otherwise throughout, mainly in understanding dissertation material and writing my prospectus. Chapters 16 and 17 are particularly excellent, dealing with epidemiological networks, epidemic percolation and dynamical systems.

[Alex Wang · Rating 3 out of 5]

Newman gives a general discussion about networks. You will see it from the first chap. about how many different real life example you can find about network. So basic mathematics. Great if you want to understand network analytics from a quantitative perspective.

[Viney Kumar · Rating 4 out of 5]

This book was a good introduction to the statistical and dynamic properties of real-world networks (or complex networks). I particularly liked the sections on centrality, poisson random graphs, and dynamical processes on networks. The emphasis on generating functions could have been reduced.

[Shuaib Choudhry · Rating 5 out of 5]

Great overview of the whole field with good references for more in depth reading and great explanations of the various terminologies of the field as well as ideas and frameworks.

[Laura del Alisal · Rating 5 out of 5]

Never thought I would enjoy reading a text book this much.

[R · Rating 5 out of 5]

Excellent book with great citations and examples. If you want to learn about networks and have a reference, I highly recommend this book.