Barabási writes with a clarity that some would argue is rare in works of a scientific nature. He explains his work in clear English, relegating any mathematical equations to footnotes for those who are interested. Power-law degree distributions and their relation to scale-free networks are at the core of his research, and thus he devotes much of the sixth chapter explaining what power-laws are, and how to identify them should you come across one in a plot of your data.
Of course, this is a book for the masses. It is not a text book. As such, he glosses over many of the intricate details and mathematics essential for a deep understanding of scale-free networks and related topics. But the book loses nothing at all by omitting these details. Rather, it allows the reader to see the much bigger picture (the underlying relationships between all kinds of different networks) which was obviously the overriding goal of this book. The book is concluded by more than thirty pages of notes, which the curious reader may peruse to obtain references to scientific publications which examine some of the concepts in much more detail.
The book is slightly repetitive, but this is perhaps inevitable when one considers the central thesis of this book: take any naturally occurring network, and the chances are it is scale-free. Thus, every direction the book takes leads back to scale-free topologies!
I would have preferred to see a little more detail. But that said, Barabási succeeds in his stated goal of taking the reader on a trip across disciplines and challenging the researcher to think in terms of networks.
There have been a lot of books recently that have been published on the new science of networks. Network theory and how it applies to many different fields from technology, marketing, biology, social science, terrorism, disease control etc. (Six Degrees by Duncan Watts, Nexus - Mark Buchanan, Smart Mobs - Howard Rheingold, Tipping Point - Malcolm Gladwell etc..).
Barabasi's is a welcome addition to the field and has a nice niche, which isn't filled by the other books. As some other reviewers have pointed this book is a popular science book, which means it covers scientific and mathematical theories at a very high level and makes these theories accessible to a wide audience. The niche lies somewhere between Gladwell's Tipping Point and Watt's Six Degrees. It is very well written and draws you in with stories that explore the theories. Some of the other reviewers have complained that Barabasi has done a disservice to the theories that he explains by making them too simplistic. I disagree, I actually found this book to be very rewarding, and a quick read, which is a sign of a well-written book. I have never been a fan of scientific and academic books that pride themselves on being totally incomprehensible. Richard Feynman, the Nobel Prize winning physicist, once said that if someone truly understands a subject they should be able to explain it to a general audience without resorting to technical jargon (Feynman's Lectures on Physics Vol 1,2,3 are a perfect example). To be able to explain a complex subject you need to resort analogies, examples and stories. Stories give a framework for the general reader to absorb the complex material. Barabasi has managed to explain the science of networks using all three. I am not sure how this can be seen as a bad thing. This exposes a wider audience to a very interesting subject; this has to be good thing.
Summary:
Anybody who loved Gladwell's Tipping Point and was looking for a book that explains some of the theories behind the phenomena will love this book. It's a little bit more technical than Gladwell's book, but it is well written and it will appeal to a wide audience. As popular science books go, this is definitely on par with Ed Regis's Nano and Steven Levy's Artificial Life, but not quite at the level of Gleick's Chaos. If you are looking for a technical book, you should look at Duncan Watt's Six Degrees, or Small Worlds.