Working with Network Data: A Data Science Perspective

James Bagrow; Yong‐Yeol Ahn

doi:10.1017/9781009212601

Working with Network Data

A Data Science Perspective

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Oddo, Matt I. B. Kobourov, Stephen and Munzner, Tamara 2025. The Census-Stub Graph Invariant Descriptor. IEEE Transactions on Visualization and Computer Graphics, Vol. 31, Issue. 3, p. 1945.

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James Bagrow, University of Vermont, Yong‐Yeol Ahn, Indiana University, Bloomington

Publisher:: Cambridge University Press
Online publication date:: June 2024
Print publication year:: 2024
Online ISBN:: 9781009212601
DOI:: https://doi.org/10.1017/9781009212601

Subjects:: Physics and Astronomy, Knowledge Management, Databases and Data Mining, Computer Science, Statistical Physics

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Drawing examples from real-world networks, this essential book traces the methods behind network analysis and explains how network data is first gathered, then processed and interpreted. The text will equip you with a toolbox of diverse methods and data modelling approaches, allowing you to quickly start making your own calculations on a huge variety of networked systems. This book sets you up to succeed, addressing the questions of what you need to know and what to do with it, when beginning to work with network data. The hands-on approach adopted throughout means that beginners quickly become capable practitioners, guided by a wealth of interesting examples that demonstrate key concepts. Exercises using real-world data extend and deepen your understanding, and develop effective working patterns in network calculations and analysis. Suitable for both graduate students and researchers across a range of disciplines, this novel text provides a fast-track to network data expertise.

‘An essential resource for newcomers to network science, this book expertly addresses the practical challenges of handling network data. Through a rich array of real-world examples and hands-on exercises, Bagrow and Ahn skillfully guide readers through the complexities of conceptualizing and analyzing networked data, making this text a fundamental tool for students and researchers eager to explore the power of connections across various disciplines.’

Albert-László Barabási - Dodge Distinguished Professor of Network Science at Northeastern University

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