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Rating: Summary: Not as wide ranging as the reviews led me to believe Review: I read the review in New Scientist, and liked the sound of this book. When it arrived I read the blurb on the back, and was further encouraged by the fact that a Sociology Professor was encouraging students to read it. I was therefore expecting a reasonably tough but rewarding read (my math is at undergraduate level and somewhat dated, but I do make an effort). Instead with the exception of a few pieces of commentary, particularly at the beginning, I found the book virtually impenetrable because of the denseness of the mathematical modelling techniques used. I suspect this is one strictly for the experts, and those with excellent post-graduate math skills.
Rating: Summary: Inspiring Review: The author believes that human thought might be a small world, in the sense that one could reach any idea if he/she finds the right associations and "short-cut"s. The small-world theory is indeed one of those short cuts itself. It links many different domains and uncovers some interesting common behavior. The theory is developed in a scientific manner with extensive numerical support. Rich literature reviews and many open questions make this book a good research reference. Complex observations are generally followed by qualitative explanations. However, some of the simpler derivations are not fully clear. I believe that adding a few lines here and there can turn this book into a textbook. The book spans many different areas of science and a deep understanding of the related results may require some background. However, each chapter ends with a brief summary, allowing the reader to move forward if he/she finds the chapter difficult. In summary, as the author puts it, the book is simply the "end of the beginning" in an exciting new field.
Rating: Summary: Inspiring Review: The author believes that human thought might be a small world, in the sense that one could reach any idea if he/she finds the right associations and "short-cut"s. The small-world theory is indeed one of those short cuts itself. It links many different domains and uncovers some interesting common behavior. The theory is developed in a scientific manner with extensive numerical support. Rich literature reviews and many open questions make this book a good research reference. Complex observations are generally followed by qualitative explanations. However, some of the simpler derivations are not fully clear. I believe that adding a few lines here and there can turn this book into a textbook. The book spans many different areas of science and a deep understanding of the related results may require some background. However, each chapter ends with a brief summary, allowing the reader to move forward if he/she finds the chapter difficult. In summary, as the author puts it, the book is simply the "end of the beginning" in an exciting new field.
Rating: Summary: Great scientific synthesis Review: The book takes a systematic look at the 'small world' graphs. These natural graphs have been discovered by graph theoretist as erly as 60's, but were not properly understood. The graphs are remarkable in their ability to cluster and scale lengths. There are fundumental connections between these graphs and complex systems, discrete dynamical systems, computation and information processing. Duncan has done a tremendous job in building experimetal and theoretical models trying to understand how these graphs come about and sustain themselves. Read this book.
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