Small Worlds: The Dynamics of Networks between Order and Randomness (Princeton Studies in Complexity) (Paperback)

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Key Phrases: logarithmic length scaling, caveman graph, random graph limit, Kevin Bacon, Moore Graph, Generalised Tit-for-Tat (more...)

Editorial Reviews

Review

Informally written and aimed at a wide audience, this book shows how mathematics yields new vistas on ubiquitous and seemingly familiar aspects of our world. -- Review

Review

An engaging and informative introduction.
(Science )

Playfully and clearly written. . . . [Watts] uses examples adroitly, and mixes abstract theory with real-world anecdotes with superb skill. . . . I have not enjoyed reading a book this much in a long time.
(Peter Kareiva Quarterly Review of Biology )

[Small Worlds] will be seized on by those seeking a first rough map of this fascinating new mathematical land. Those entering can expect to find some amazing connections between areas of research with apparently nothing in common, such as neurology to business studies. But then, it's a small world.
(Robert Matthews New Scientist )

Informally written and aimed at a wide audience, this book shows how mathematics yields new vistas on ubiquitous and seemingly familiar aspects of our world.
(Choice )

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Product Details

• Paperback: 264 pages
• Publisher: Princeton University Press; illustrated edition edition (November 24, 2003)
• Language: English
• ISBN-10: 0691117047
• ISBN-13: 978-0691117041
• Product Dimensions: 9.1 x 6.1 x 0.7 inches
• Shipping Weight: 13.4 ounces (View shipping rates and policies)
• Average Customer Review: 3.1 out of 5 stars  See all reviews (8 customer reviews)
• Amazon.com Sales Rank: #501,858 in Books (See Bestsellers in Books)

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Customer Reviews

Most Helpful Customer Reviews

72 of 78 people found the following review helpful:

3.0 out of 5 stars Not as wide ranging as the reviews led me to believe, March 14, 2000

By	P MARTIN (Hertfordshire, UK) - See all my reviews

This review is from: Small Worlds (Hardcover)

I read the review in New Scientist, and liked the sound of this book. When it arrived I read the blurb on the back, and was further encouraged by the fact that a Sociology Professor was encouraging students to read it. I was therefore expecting a reasonably tough but rewarding read (my math is at undergraduate level and somewhat dated, but I do make an effort). Instead with the exception of a few pieces of commentary, particularly at the beginning, I found the book virtually impenetrable because of the denseness of the mathematical modelling techniques used. I suspect this is one strictly for the experts, and those with excellent post-graduate math skills.

16 of 18 people found the following review helpful:

2.0 out of 5 stars Not enough contents to be a good book, July 7, 2005

By	Zac (USA) - See all my reviews

This review is from: Small Worlds (Hardcover)

Networks are since a couple of years object of intense research in several different disciplines. One reason therefore is certainly the outstanding article by Watts and Strogatz, Collective dynamics of small world networks, Nature, 393:440--442, 1998. Unfortunatelly, this book can not continue the high level of this article. Actually, it does not really provide much more information than the article itself. I would suggest to read the article cited above and either decide for another book or to look directly in the literature and read the origninal articles.

To summarize, this book is not terribly weak, but one can clearly sees that it swims on the current 'complex networks' wave without providing enough justification for its existence. Of course, if you do not have access to the original literature and just what to have a general overview of complex networks and what be done with them, you may consider buying this book.

13 of 15 people found the following review helpful:

4.0 out of 5 stars Inspiring, July 23, 2001

By	Farzad Etemadi "farzad3" (Aliso Viejo, Ca USA) - See all my reviews

This review is from: Small Worlds (Hardcover)

The author believes that human thought might be a small world, in the sense that one could reach any idea if he/she finds the right associations and "short-cut"s. The small-world theory is indeed one of those short cuts itself. It links many different domains and uncovers some interesting common behavior.

The theory is developed in a scientific manner with extensive numerical support. Rich literature reviews and many open questions make this book a good research reference. Complex observations are generally followed by qualitative explanations. However, some of the simpler derivations are not fully clear. I believe that adding a few lines here and there can turn this book into a textbook.

The book spans many different areas of science and a deep understanding of the related results may require some background. However, each chapter ends with a brief summary, allowing the reader to move forward if he/she finds the chapter difficult. In summary, as the author puts it, the book is simply the "end of the beginning" in an exciting new field.