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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.
List of contents
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.
About the author
Vito Latora is Professor of Applied Mathematics and Chair of Complex Systems at Queen Mary University of London. Noted for his research in statistical physics and in complex networks, his current interests include time-varying and multiplex networks, and their applications to socio-economic systems and to the human brain.
Summary
Including real-world data sets and ready-to-use software tools, this book encourages hands-on experimentation with complex network data. Students are guided through varying levels of complexity to gain a deep understanding of the basics and applications of network theory, making this an ideal university-level textbook for students across the scientific disciplines.
Report
'This is a substantial text which will serve a broad section of readers who wish to gain insights into complex networks. Some effort will be needed to get the most out of this book but the reader who expends that effort will be well-rewarded. In turn, the authors are to be congratulated for the effort that they have made to produce such a delightful text.' K. Alan Shore, Contemporary Physics
