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Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life

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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. In Linked, Albert-László Barabási, the nation’s foremost expert in the new science of networks, takes us on an intellectual adventure to prove that social networks, corporations, and living organisms are more similar than previously thought. Barabási shows that 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.

How is the human brain like the AIDS epidemic? Ask physicist Albert-László Barabási and he’ll explain them both in terms of networks of individual nodes connected via complex but understandable relationships. Linked: The New Science of Networks is his bright, accessible guide to the fundamentals underlying neurology, epidemiology, Internet traffic, and many other fields united by complexity.

Barabási’s gift for concrete, nonmathematical explanations and penchant for eccentric humor would make the book thoroughly enjoyable even if the content weren’t engaging. But the results of Barabási’s research into the behavior of networks are deeply compelling. Not all networks are created equal, he says, and he shows how even fairly robust systems like the Internet could be crippled by taking out a few super-connected nodes, or hubs. His mathematical descriptions of this behavior are helping doctors, programmers, and security professionals design systems better suited to their needs. Linked presents the next step in complexity theory–from understanding chaos to practical applications. –Rob Lightner

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