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A cocktail party? A terrorist cell? Ancient bacteria? An international conglomerate?
All are networks, and all are a part of a surprising scientific revolution. Albert-László Barabási, the nation’s foremost expert in the new science of networks and author of Bursts, takes us on an intellectual adventure to prove that social networks, corporations, and living organisms are more similar than previously thought. Grasping a full understanding of network science will someday allow us to design blue-chip businesses, stop the outbreak of deadly diseases, and influence the exchange of ideas and information. Just as James Gleick and the Erdos–Rényi model brought the discovery of chaos theory to the general public, Linked tells the story of the true science of the future and of experiments in statistical mechanics on the internet, all vital parts of what would eventually be called the Barabási–Albert model.
- Sales Rank: #631954 in Books
- Published on: 2003-04-29
- Released on: 2003-04-29
- Original language: English
- Number of items: 1
- Dimensions: 8.52" h x .69" w x 5.58" l, .63 pounds
- Binding: Paperback
- 304 pages
Review
"A sweeping look at a new and exciting science." —Donald Kennedy, Editor-in-Chief, Science Magazine
"Captivating…Linked is a playful, even exuberant romp through an exciting new field." —Time Out New York
About the Author
Albert-László Barabási is a pioneer of real-world network theory and author of the bestseller, Linked: How Everything is Connected to Everything Else and What It Means for Business, Science, and Everyday Life. At 32, he was the youngest professor to be named the Emil T. Hofmann Professor of Physics at the University of Notre Dame and has won numerous awards for his work, including the FEBS Anniversary Prize for Systems Biology and the John von Neumann Medal for outstanding achievements. He currently lives in Boston and is Distinguished Professor and Director of the Center for Network Science at Northeastern University.
Most helpful customer reviews
28 of 29 people found the following review helpful.
An intellectual memoir
By algo41
Linked focuses on network theory and some of its applications, where networks are defined as dynamic linear graphs. It is written for the non-mathematicians, and in fact does a very good job of giving the reader insight into how the mathematical modeler thinks and works, and what mathematical modeling is (the phrase "dynamic linear graphs" does not actually appear in the text). "Linked" is kind of an intellectual memoir, and especially in the first few chapters, is charming as well as informative. The problem is that Barabasi has an inflated view of the importance and primacy of his work and interests vis-a-vis the general subject of the theory of complex systems. Also, while Barbasi strikes me as intellectually honest, his lack of knowledge of such subjects as cellular biology leads him to erroneous claims for what insights may be attributed to recent work in network modeling. He is on stronger grounds when he discusses narrow subjects such as the links between corporate directors, and Barabasi does seem to know quite a bit about sociological modeling and the Internet. In terms of intellectual stimulation and excitement, Linked does not begin to match up with Emergence: The Connected Lives of Ants, Brains, Cities, and Software by Steven Johnson, and I guess I was expecting something more comparable to that book.
42 of 47 people found the following review helpful.
Book's Audience: Who should be linked to this book.
By K. Sampanthar
I have focused this review on the audience of the book, since other reviews have quite adequately summarized the material.
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.
17 of 20 people found the following review helpful.
Reduction to nodes and links
By Professor Joseph L. McCauley
Albert Barabasi presents the lay reader with a stimulating description of the origins of network theory and recent applications. He describes random networks, small world and scalefree networks. In nonrandom networks the importance of hubs is emphasized. Small world networks are the ones with a well defined averge number of links, and in scalefree ones the density of links scales as a power law. For the many interesting examples discussed, I would like to have seen graphs showing scaling over at least three decades in order to be convinced of scaling. However, in practice, whether a network scales or not may not be so important. I liked best the discussions of terrorism, AIDS, and biology. If one could locate the hubs, then a small world network could be destroyed, but as the author points out there is no systematic method for locating the hubs. Also, destroyed hubs in a terror network might be replaced rather fast, whereas airline hubs could not be replaced so quickly. The book might be seen as indicating a starting point to try to develop a branch of mathematical sociology. For example, the maintainance of ethnic identity outside the Heimat is discussed in terms of networking. Now for a little criticism.
I did not find the discussion of ‚the rich get richer` very helpful because network theory at this stage deals only with static geometry, not with empirically-based dynamics. In fact, the dynamics of financial markets have been described empirically accurately without using any notion of networking. In the text the phrase „economic stability" is used but stability is a dynamic idea, and there is no known empirical evidence from the analysis of real markets for any kind of stability. The absence of dynamics on networks means that complexity is not described at all: there is nothing complex about the geometry of a static network! Suggesting that cell biology can be described by networking is empty so long as dynamics are not deduced from empirics. Nonempirical models of dynamics will probably not be of much use for making advances in understanding or treating cancer, e.g. Everything we know about cell biology and cancer was discovered via reductionism, by isolating cause and effect the way that a good auto mechanic does in order to repair a car.
Unfortunately, the author lets his enthusiasm get the best of him when he proclaims „laws of self-organization" and the need to go beyond reductionism. First, there are no known laws of „self-organization". The only known laws of nature are the laws of physics and consequences deduced from the laws, namely, chemistry and cell biology. Worse, every mathematical model that can be written down is a form of reductionism. Quantum theory reduces phenomena to (explains phenomena via) atoms and molecules. All of chemistry is about that. Cell biology attempts to reduce observed phenomena to DNA, proteins, and cells. Believers in self-organized criticality try to reduce the important features of nature to the equivalent of sandpiles. Network enthusiasts hope to reduce phenomena to nodes and links. In order to try to isolate cause and effect, there is no escape from reductionism of one form or another, holism being an empty illusion. So I did not at all like the assertion on pg. 200 that globalization (via deregulation and privatization) is inevitable, because there is no law that tells us that it is.
Summarizng: there is no complexity without dynamics, there are no known „laws of self-organization", and reductionism is the only hope for doing science. Anyone who disagrees with this is welcome to explain to me and others the alternative (jmccauley@uh.edu).
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