Nice introductory book on Network Science.

As a student of mathematical modeling, I found this book thought-provoking and interesting. Not a stranger to networks, I would say this book still managed to have some effect on me. It would be enough for me to credit this book with re-sparking my interest in the topics of network analysis and mathematical models.

A bit on the long-winded side at times, however. But this might be because it is not my first time with networks.

3.5-4/5 ( )

The subtitle is a pretty good summary of the premise of this book. It explores the theoretical underpinnings of things being linked (referencing, for example, the Königsberg Bridge problem) and then explores how things are linked in nature as opposed to in social structures; the major distinction is that in nature, the number of “links” held by a given thing tends to be bell-curve distributed, whereas in socially-designed phenomena, it’s more of a y = 1/x sort of “the limit does not exist” on the tail end, allowing for “hubs.” This applies not only to social structure, but genetics, airline routes, the internet, and the Kevin Bacon game.

The finding is that if you have a dense network, picking a network node at random and eliminating it will not bring down the network… even if you do so for something like 80% of the network. But removing just 15-20% of the network hubs will cause the whole thing to come crashing down. ( )

I read this book several years ago, when I was closing up my University studies. It opened my mind to new research opportunities that I have then undertaken for my ph.d.
The book gives a very nice introduction to the world of complex network, covering the random models and moving on to what the authors have discovered and named scale-free organization.
The mathematics are far from being heavy and down-to-the-ground examples are always reported to help the reader connecting to her daily life.
A very nice book! ( )

This is one of the most pleasant scientific reads in form of a book I have the pleasure to read had. The introduction to networks is very clever, not starting directly with science but rather introudcing all the basic and necessary conceptd, scientists and problems present in network theory. Hving presentef this the authors describes network research from a chronological poont of view, where it is very easy to understand all the new discovered concepts and the necessity of them. I have rarely had access to such pleasant literature. The book finishes describing thet last advances in network theory and paves the ground for the next conceptual step, which is networks dynamics.

My only concern is whether his papers are so well written and whether other books like this can be easily found in research areas that interest me like quantum interactions, doking, and so on.

It would have been really difficult to read from scratch a paper from this Albertq, without all this interesting introductions.

Now i am going to check the current status of his research and start to think how my research could benefit from his insights. ( )

I cannot say I understood fully all that Barabási had to say, or even was able to retain all that thought I understood at the time I read it, but still and all, I am extremely glad I tackled his books. It is really quite readable! He begins it so gently, carrying even the non-mathematicians, non-physicists, and non-scientists into more and more complexity. Our understanding of our world is gaining on our ignorance! I feel I need to at least make an attempt to keep up! ( )

excelent ( )

A good introductory book about networks and its role in our life. Some parts are a litte bit dry but in general an enjoyable work. ( )

A fascinating book about the intersection of graph theory and real life. ( )

An interesting book on network theory. The author nicely takes you through the evolutions of thought around the ways networks are organized, building up to the current theory of complex networks that relatively accurately models things like the internet. Complex networks are arranged with links between nodes. If we're thinking about the internet, then each node is a website and the links are the, well, links between them. Different nodes have different levels of fitness (mathematically defined as the likelyhood that it will be linked to, but practically just how good is the website), resulting in certain nodes (ex. Google, Amazon, Wikipedia) becoming hubs in the network, doing much of the work of interconnectivity for the entire thing.

The book lays out this theoretical framework very well, and it does seem accurate. The most interesting thing about the book to me, though, was its discussion of some of the implications of this. The existence of hubs means that the connectivity of a network is inordinately maintained by certain nodes and that means that those nodes are critical if you want to either protect or destroy the network. This means, for example, that some banks could be "too big to fail," because if their connectivity were lost the entire system would go out. Even more problematic, I thought, was Barbasi's discussion of the AIDS virus - HIV spreads through a network of sexual connectivity that follows this network pattern. To stop the spread of the disease you would want to interrupt this network. If there is limited treatment available (as there is in many parts of Africa, for example) network theory requires that the most promiscuous nodes have priority for treatment. Logical, but ethically weird to me.

Anyway, overall this was a very good book. It explained its topic well and gave me plenty to think about. Four stars. ( )

A good introduction to network science. Barabási explains the sequence of insights that led to recent insights into the properties of scale-free networks, which show up everywhere from the Internet to cellular biology. This is just an overview; the copious notes in back provide starting points if you want to delve further into the field. ( )

Superficial overview. ( )

For me the book went too far in story telling details: I was bored by the small details of who did what in the morning of a day before doing something that the writer would like to mention. And generally, the whole book could have been shorter.

It was interesting to read about he topology of networks for a while, but when he started talking about the revolution these things will make to science (actually, he mentiones areas specifically), well, then I felt that this reminds me a hype. Of course, I cannot judge it, but he didn't convince me.

E.g. he starts talking about September the 11th, terrorists networks, coming to the conclusion - without using practically any knowledge of networks - that the only way of stopping terrorists is to cease the causes, so that noone wants to join a terrorists network. Yes, that would really be a revolution. ( )

interesting book on how different networks perform in similar ways. Author discusses biological networks, computer networks, people networks, discusses how different networks have different characteristics as, there are three main architectures of networ

Pretty good.

I love reading about accessible abstract ways of interpreting all sorts of phenomena. ( )

Linked: The New Science of Networks (Hardcover)
by Albert-Laszlo Barabasi

"Brief History of The Future"
Preferential Attachment
Cascading Failure
Parasitic Computing
Directed Network
The Internet Archive
Diffusion of AIDS Epidemic
Perculation Theory
Scale Free Network
Social Link
P53 Molecule
The Königsberg Bridge problem

Topics
Alfréd Rényi (March 20, 1921 – February 1, 1970) was a Hungarian mathematician who made contributions in combinatorics and graph theory but mostly in probability theory.
Leonhard Paul Euler(1707– 1783) was a pioneering Swiss mathematician and physicist, who spent most of his life in Russia and Germany.
Doctors selection of a new drug.
In social links, some individuals are super-connected; they are super-hubs. For a new idea/product to spread, the social super-hubs must be targeted.
Failure of Apple Newton caused by rejection of opinion leaders, early adopters.
AIDS epidemic spread via a super-hub French Canadian.
Personalize medicine in the future only attack the abnormality with no side effect.
We need to look at a cell as a scale free network.
P53 Molecule suppresses cancer cell spread.
The network of corporate board of directors in US companies.
Major pharmaceutical companies are linked to small research companies in a web of partneships. The hubs are the big pharmas.
Global finance is a scale free network of financial institutions; the economic melt down in Asia started with a small bank in Thailand. Understanding networks will help prevent cascading failures. ( )

After reading Mitchel Resnick's Turtles, Termites, and Traffic Jams: Explorations in Massively Parallel Microworlds (Complex Adaptive Systems), my exploration of decentralized networks went down a very viral path. This book, in particular, discusses the application of network theory in the context of its historical significance. The author explores how it can be used as a tool and device to understand cities, computer networks social networks, human-human interactions (speech), human-computer interactions (HCI), computer-computer interactions (protocol), diseases, computer viruses, nature. Based on this book and its related siblings, it inspires tremendous amounts of ideas for the next big thing in marketing strategy. ( )

This book is an excellent basic overview of important links. I learned about graph theory and methods to reduce the spread of AIDS.
fascinating. ( )

The phenomenon of networks in everyday life: from social networks to the web. How networks are organized and how they change, react to attacks or why they sometimes collapse. Nicely told with examples out of politics, maths, and mostly from the web. ( )

http://malaysianatheist.blogspot.com ( )

Overall I enjoyed this book, but I found the examples from the social sciences most compelling because this was my interest in the book. I borrowed this book from the Stillwater Public Library. ( )

The third (in order of reading by me) recent book on "small worlds" and related stuff such as WWW structure.

4 ( )