Downloaded from https://academic.oup.com/comnet/article-abstract/6/5/830/4793701 by Ed 'DeepDyve' Gillespie user on 17 October 2018 Journal of Complex Networks (2018) 6, 830 doi: 10.1093/comnet/cnx062 Advance Access Publication on 8 January 2018 Book Review Complex Networks: Principles, Methods and Applications by Vito Latora, Vincenzo Nicosia and Giovanni Russo Cambridge University Press, £54.99, ISBN: 9781107103184 Reviewed by Guido Caldarelli IMT Alti Studi Lucca, Piazza S. Francesco 19, 55100 Lucca, Italy Corresponding author. Email: Guido.Caldarelli@imtlucca.it Edited by: Ernesto Estrada The book presented today has a long story. I know personally the ﬁrst author of this book also because he is one of the editors of this journal. The ﬁrst mention of this book was about 10 years ago when he started to work at the ﬁrst draft. Ten years have then passed, and tens of other textbooks, books and review papers have appeared on the same topic in the meanwhile. Now that the book is published, I can perfectly understand why it took 10 years of work to ﬁnish it. The book is an encyclopaedic effort, since it presents a detailed overview of the theory and methods of network science, and covers, at the same time, the mathematics of networks as well as real-world data sets, network models and graph algorithms. The book covers a large variety of topics, including elements of graph theory, and ideas, such as those of centrality and centralization, coming from the social networks community. It discusses in details the main properties that characterise the architecture of a complex network, and the principles that are common to networks from different ﬁelds. It then introduces the reader to the art of network modelling, with detailed accounts on the mathematics of random graphs, on small-world and scale-free networks, and on various models of growing graphs. The last four chapters of the book are devoted to four more advance topics, namely networks with degree-degree correlations, motif analysis, community structure and weighted networks. The book does not cover processes on networks, a topic that, as explicitly mentioned by the authors, has been left to an entire second book, which I hope will soon follow this one. The book contains also several network data sets and original examples, ranging from children friendships at Elisa’s kindergarten, to collaborations in science or citations among scientiﬁc articles, and to historically famous networks such as the Zachary’s karate club or the neural network of Caenorhabditis elegans. It also discusses practical applications such as, how to identify the functional regions of a neural network or the hot places of a city, how to determine whether a football team is well balanced or not in terms of the ways its players are passing each others the ball, or how to construct a well-diversiﬁed portfolio by understanding correlations among stocks in a ﬁnancial market. The book is mathematically rigorous; however, due to its colloquial style and engaging presentation, it is also a very pleasant read. Although, it has been designed primarily as a textbook for a ﬁrst undergraduate and/or postgraduate taught module on complex networks analysis and modelling, the book can be used at different levels. It can be handy as a practical book to be used as a working tool by practitioners in network science. I am sure it will become a reference text in the library of many researchers and students in physics, mathematics, engineering, biology, neuroscience and social sciences. © The authors 2018. Published by Oxford University Press. All rights reserved.
Journal of Complex Networks – Oxford University Press
Published: Oct 1, 2018
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