
As an Amazon Associate and affiliate partner, Menrva Books earns from qualifying purchases. Learn more
This book provides a comprehensive yet short description of the basic concepts of Complex Network theory. In contrast to other books the authors present these concepts through real case studies. The application topics span from Foodwebs, to the Internet, the World Wide Web and the Social Networks, passing through the International Trade Web and Financial time series. The final part is devoted to definition and implementation of the most important network models.The text provides information on the structure of the data and on the quality of available datasets. Furthermore it provides a series of codes to allow immediate implementation of what is theoretically described in the book. Readers already used to the concepts introduced in this book can learn the art of coding in Python by using the online material. To this purpose the authors have set up a dedicated web site where readers can download and test the codes. The whole project is aimed as a learning tool for scientists and practitioners, enabling them to begin working instantly in the field of Complex Networks.
This book investigates the practical application of complex network theory by bridging theoretical concepts with real-world data analysis using Python. Alessandro Chessa and Guido Caldarelli leverage their expertise to provide a framework that moves beyond abstract mathematics into functional implementation. By utilizing diverse datasets ranging from biological foodwebs to global financial systems, the authors demonstrate how to quantify and model complex structures. The text serves as a technical manual for scientists and practitioners seeking to apply network analysis to empirical problems.
What You Will Find
Experts highlight this work as a functional resource for practitioners who require immediate, code-based applications of network theory. Readers frequently note the balance between concise theoretical explanations and the utility of the provided online Python repositories.
Page Count:
136
Publication Date:
2016-11-15
Publisher:
Oxford University Press
ISBN-10:
0199639604
ISBN-13:
9780199639601
No comments yet. Be the first to share your thoughts!