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Small Worlds [Hardcover]

Duncan J. Watts (Author)
3.4 out of 5 stars  See all reviews (7 customer reviews)


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Book Description

Princeton Studies in Complexity August 23, 1999
Everyone knows the small-world phenomenon: soon after meeting a stranger, we are surprised to discover that we have a mutual friend, or we are connected through a short chain of acquaintances. In his book, Duncan Watts uses this intriguing phenomenon--colloquially called "six degrees of separation"--as a prelude to a more general exploration: under what conditions can a small world arise in any kind of network?

The networks of this story are everywhere: the brain is a network of neurons; organisations are people networks; the global economy is a network of national economies, which are networks of markets, which are in turn networks of interacting producers and consumers. Food webs, ecosystems, and the Internet can all be represented as networks, as can strategies for solving a problem, topics in a conversation, and even words in a language. Many of these networks, the author claims, will turn out to be small worlds.

How do such networks matter? Simply put, local actions can have global consequences, and the relationship between local and global dynamics depends critically on the network's structure. Watts illustrates the subtleties of this relationship using a variety of simple models---the spread of infectious disease through a structured population; the evolution of cooperation in game theory; the computational capacity of cellular automata; and the sychronisation of coupled phase-oscillators.

Watts's novel approach is relevant to many problems that deal with network connectivity and complex systems' behaviour in general: How do diseases (or rumours) spread through social networks? How does cooperation evolve in large groups? How do cascading failures propagate through large power grids, or financial systems? What is the most efficient architecture for an organisation, or for a communications network? This fascinating exploration will be fruitful in a remarkable variety of fields, including physics and mathematics, as well as sociology, economics, and biology.



Editorial Reviews

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, it¹s 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 )

Review

Duncan Watts has created that rarity of rarities: a book with enough fascinating facts and stories to keep the casual reader turning the pages coupled with enough engaging detail to satisfy the most technically sophisticated reader. Thus, whether you are just curious about the world around you or eager to begin your own small-world research, this is the definitive guide to the fascinating and profound world of small-world networks. (William L. Ditto, Applied Chaos Laboratory, Georgia Institute of Technology )

Product Details

  • Hardcover: 266 pages
  • Publisher: Princeton University Press (August 23, 1999)
  • Language: English
  • ISBN-10: 0691005419
  • ISBN-13: 978-0691005416
  • Product Dimensions: 9.5 x 6.4 x 0.9 inches
  • Shipping Weight: 1.2 pounds
  • Average Customer Review: 3.4 out of 5 stars  See all reviews (7 customer reviews)
  • Amazon Best Sellers Rank: #1,301,411 in Books (See Top 100 in Books)

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Customer Reviews

7 Reviews
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Average Customer Review
3.4 out of 5 stars (7 customer reviews)
 
 
 
 
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81 of 89 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.
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19 of 22 people found the following review helpful:
2.0 out of 5 stars Not enough contents to be a good book, July 7, 2005
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.
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6 of 6 people found the following review helpful:
2.0 out of 5 stars Hard, August 11, 2008
This book is very hard for non-numerate individuals (like myself, a law student). I picked it up after reading Six Degrees: The Science of a Connected Age (Open Market Edition), hoping I would find longer - but equally accessible - explanations of those concepts that are sketched in the latter.
Unfortunately, I didn't. The book is essentially a presentation of the modelling techniques used by Prof. Watts in arriving to the theory of Small Worlds. A thorouhg understanding would require truly firm foundations in statistics, graph theory and topology. Without that, you'll probably be able to understand at most twenty pages (out of 241).
If you have read Six Degrees, you'll still find some useful and still accessible discussion on multidimensional scaling, i.e. on the problem of measuring social distance, which Watts later discusses in Six Degrees with reference to the problem of search in networks. However, that's just about it.
My two-star rating is by no means meant to criticise Prof. Watts's ideas, or the substantial contentions he makes in the book (very few of which I was able to understand from a mathematical point of view, due to my faulty background). Deserving two starts, instead, are the Editorial reviews, which are hugely misleading. This is not "aimed at a wide audience". Or, better, it is aimed at a wide audience of MATHEMATICIANS. It is a technical one, and that would need to be made explicit.
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Inside This Book (learn more)
First Sentence:
The Kevin Bacon Game is a curious thing to be sure. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
logarithmic length scaling, caveman graph, random graph limit, global entrainment, spatial graphs, equivalent random graph, characteristic path length, coupling topology, global length scale, density classification task, relational graphs, unconditional defectors, random limit, unbiased performance, random substrate, tree substrate, conditional cooperators, clustering coefficient, local length scale, ring substrate, collaboration graph, clustered graphs, global edges, random graph theory, finite cutoff
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Kevin Bacon, Moore Graph, Generalised Tit-for-Tat, Scaled Length, Numerical Analytical, Scaled Clustering, United States, Cauchy Graphs, Western States Power Graph, Caveman Substrate, Clustering Coefficient Figure
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