Complex Networks Principles, Methods and Applications A comprehensive introduction to the theory and applications of complex network science, complete with real-world data sets and software tools. Vito Latora (Author), Vincenzo Nicosia (Author), Giovanni Russo (Author) 9781107103184, Cambridge University Press Hardback, published 28 September 2017 584 pages, 220 b/w illus. 25 tables 58 exercises25.3 x 19.4 x 2.8 cm, 1.41 kg 'Thanks to its colloquial style, the extensive use of examples and the accompanying software tools and network data sets, this book is the ideal university-level textbook for a first module on complex networks. It can also be used as a comprehensive reference for researchers in mathematics, physics, engineering, biology and social sciences, or as a historical introduction to the main findings of one of the most active interdisciplinary research fields of the moment.' Mathematical Reviews Clippings Networks constitute the backbone of complex systems, from the human brain to computer communications, transport infrastructures to online social systems and metabolic reactions to financial markets. Characterising their structure improves our understanding of the physical, biological, economic and social phenomena that shape our world. Rigorous and thorough, this textbook presents a detailed overview of the new theory and methods of network science. Covering algorithms for graph exploration, node ranking and network generation, among others, the book allows students to experiment with network models and real-world data sets, providing them with a deep understanding of the basics of network theory and its practical applications. Systems of growing complexity are examined in detail, challenging students to increase their level of skill. An engaging presentation of the important principles of network science makes this the perfect reference for researchers and undergraduate and graduate students in physics, mathematics, engineering, biology, neuroscience and the social sciences. Preface Introduction 1. Graphs and graph theory 2. Centrality measures 3. Random graphs 4. Small-world networks 5. Generalised random graphs 6. Models of growing graphs 7. Degree correlations 8. Cycles and motifs 9. Community structure 10. Weighted networks Appendix References Author index Index. Subject Areas: Computer networking & communications [UT], Mathematical physics [PHU], Physics [PH], Mathematical modelling [PBWH], Complex analysis, complex variables [PBKD], Mathematics [PB]
