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Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life (Anglais) Broché – 29 avril 2003

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Descriptions du produit

Revue de presse

"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

Biographie de l'auteur

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.

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Format: Broché Achat vérifié
L'auteur est clair et précis, il nous entraîne dans une courte histoire du développement de la science des réseaux (ou plutôt de l'étude des réseaux par différentes sciences, de la physique à la sociologie politique), toutes les anecdotes sur les scientifiques sont plutot rigolotes et ce livre donne un aperçu très intéressant des applications possibles des modélisations portant sur les réseaux... bref un bon point de départ !
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Commentaires client les plus utiles sur Amazon.com (beta)

Amazon.com: 4.2 étoiles sur 5 162 commentaires
4 internautes sur 4 ont trouvé ce commentaire utile 
3.0 étoiles sur 5 Show's the point in 100,000 words, when only 10,000 were needed. 3 mars 2015
Par My Pleasure - Publié sur Amazon.com
Format: Broché Achat vérifié
What it says is true and it is extremely informative (almost too much so) because each chapter is the same practically; and if you've studied much about networks or sociology at all, many of it is already secondary. Good book for people who want a lot of needless text.
5 internautes sur 5 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Dull title, superb book 18 avril 2010
Par Camber - Publié sur Amazon.com
Format: Broché Achat vérifié
This book describes the emergence of an important new area of science, and it's written by Alberto-Laszlo Barabasi, one of the pioneers and leaders in the field. The writing is clear and engaging, so the book should be fairly easy to read by general readers reasonably comfortable with science. Accommodating such a broad audience does limit the technical depth, but there's still plenty of detail, and the book has abundant endnotes which go into further detail and also link the book with the professional literature (pun intended).

The systematic presentation of the book makes it fairly easy to summarize:

(1) Many systems are complex, and thus are not amenable to conventional reductionism. Instead, complex systems typically involve networks.

(2) The study of networks began with "simple" graph theory, and then progressed to random networks in which most nodes have the about the same number of links.

(3) Real-world networks tend to be "small worlds" in the sense that the shortest path from a given node to any other node is typically only several links. This is the case even for networks with millions or billions of nodes.

(4) Rather than being entirely random, real-world networks tend to display clustering, with "weak links" between clusters. These weak links, which may be random, are the key to making these networks small worlds.

(5) Small-world networks tend to have a minority of highly-linked "hub" nodes which shorten the average path between nodes. More precisely, such networks tend to have a hierarchical scale-free structure (topology) which follows a power law with an exponent of 2 to 3, such that there are many nodes with few links and progressively fewer nodes as the number of links per node increases (again, hub nodes have the most links). (By the way, the ratings of this book roughly follow a power law distribution.)

(6) Scale-free structure in networks is largely the result of a preferential attachment process in which well-connected and competitively fitter nodes have a greater ability to attract further links as the network grows ("the rich get richer"). If a single node has dominant fitness, a "winner takes all" effect can occur in which the network develops a star structure rather than a scale-free structure.

(7) Unlike random networks, scale-free networks are robust against even a large number of random removals of nodes. This is largely because the minority of hub nodes keeps the network connected. However, targeted removal of several hub nodes (~5% to 15%) can cause a scale-free network to collapse (loose connectivity), thus making such networks vulnerable to attack. The problem is compounded if such networks are vulnerable to cascading failures.

(8) Viruses, fads, information, etc. can readily spread in scale-free networks because there is no minimum threshold which the spreading rate needs to exceed.

(9) Because the links in the Web are directed, the Web doesn't form a single homogeneous network, but rather has a fragmented structure involving four major "continents" and some "islands", and there is fragmentation within these continents as well.

(10) Behavior of living cells is controlled by multiple layers of networks, including regulatory and metabolic networks. These networks typically have a scale-free structure with an average path length of about three. Across organisms, the hubs in these networks tend to be the same, but the other nodes (molecules) vary widely. This is why targeting drugs at hubs can be both effective and can have side effects (presumably, the key is to find and target hubs which are specific to disease states, if such hubs exist).

(11) The economy is a network in which hub organizations tend to accumulate links as the network grows by absorbing smaller nodes through mergers and acquisitions.

(12) Highly "optimized" organizations with a tight hierarchy tend to be less adaptive than networked organizations, and thus susceptible to failure.

(13) Networked economies are susceptible to cascading failures, especially when the hubs become "too big to fail" (Barabasi's warning here was of course all too accurate).

(14) Real networks tend to have a hierarchically modular structure, while still being scale-free.

The only significant "negative" is that this book came out in 2002/2003, whereas network science has continued to develop since then. However, Barabasi has another book (Bursts: The Hidden Pattern Behind Everything We Do) coming out in just a few weeks, which should bring us up to date, and it makes sense to read "Linked" first, so that you can start at the beginning. Very highly recommended.
5.0 étoiles sur 5 Mapping the Internet 14 mai 2012
Par Nick Danger - Publié sur Amazon.com
Format: Broché Achat vérifié
This book is about the peculiar results obtained when the author set out to "map the internet". Just as we have maps of cities and towns it would be useful to know how to get from here to there via electronic means. One of the premises is that most people don't know that someone somewhere has produced information and published it to the internet unless your part of that "community". The author goes into detail about how new information is constantly being produced but that we can't find it unless it is connected thru "hubs" that many of us connect to in various ways (google, amazon, etc.). These hubs provide links to other hubs that in turn lead us to other hubs. Its all about dissemination of information. Why do some videos go viral and others never even get started? They make reference to the game "6 Degrees of Kevin Bacon" to illustate how all of us are loosely connected in very short distances via particular routes. For example we all know someone that everyone knows for some reason or another. I wonder aloud how this field will boom into a science and how retailers will exploit it. I remember a line from a book about the Manhatten Project that says something to the effect that "technology itself in not inherently good or bad, its the implementation of technology that causes the distinction." You can't tell me that sharing all that information on Facebook doesn't have some negative consequences.
4.0 étoiles sur 5 I found the book quite interesting. You don't need ... 5 octobre 2014
Par Roger Doger - Publié sur Amazon.com
Format: Format Kindle Achat vérifié
I found the book quite interesting. You don't need to be an expert math person to understand it. The book examines many types of networks such as webpages, citation networks, molecule delays, Airline Routing, Income Distribution, Popular Press Literature, Distance over which atoms communicate, Phase transitions in materials, and Experimental data. These are examples of Power Distribution and not Bell Curve distribution networks, as most people believe them to be. The author explains in detail how the different types of networks can be sensitive to deliberate forms of attack. It is interesting how the internet just expanded by its self and became organized in a way no one expected.
4.0 étoiles sur 5 Very impressed, picked up new ideas. 10 mars 2012
Par Glenn D. Robinson - Publié sur Amazon.com
Format: Broché Achat vérifié
Very impressed with this book on how people, organizations and other things are linked. We have all heard of 6 degrees of Kevin Bacon, yet the author writes it is less than 3 degrees of Kevin Bacon. Using the internet to find the connections of networks, the studies have improved. The first study of the power of networking can go back to St Paul and the spread of Christianity. Later examples are the Air France Flight Attendant who spread AIDS, the many internet viruses and the 9/11 terrorists. Using these, how do we use our own networks? The fact is the power is actually not from our primary network, but our secondary network. The reason being is that our primary network has too much ego and history built in for much change, but the secondary network does not. While this book was written in 2002 and is probably outdated in some reagard (as much more data has obeen accumalted since), it is very fascinating and worth the read.
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