Complex Networks: Principles, Methods and Applications - Hardcover

Latora, Vito; Nicosia, Vincenzo; Russo, Giovanni

Hardcover

ISBN 10: 1107103185 ISBN 13: 9781107103184

Publisher: Cambridge University Press, 2017

Synopsis

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.

About this title

Book Description

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.

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.

Edition details

• Publisher: Cambridge University Press
• Publication date: 2017
• ISBN 10: 1107103185
• ISBN 13: 9781107103184
• Binding: Hardcover
• Language: English
• Edition number: 1
• Number of pages: 594