Working with Network Data by James Bagrow and Yong‐Yeol Ahn (2024, Hardcover)

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About this product

Product Identifiers

PublisherCambridge University Press
ISBN-101009212591
ISBN-139781009212595
eBay Product ID (ePID)2336606939

Product Key Features

Book TitleWorking with Network Data
Number of Pages400 Pages
LanguageEnglish
Publication Year2024
TopicEngineering (General), Physics / Mathematical & Computational
IllustratorYes
GenreTechnology & Engineering, Science
AuthorJames Bagrow, Yong‐Yeol Ahn
FormatHardcover

Dimensions

Item Height1.4 in
Item Length9.9 in
Item Width7 in

Additional Product Features

LCCN2023-054233
Dewey Edition23/eng/20240508
Reviews'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
Dewey Decimal004.6/5
Table Of ContentContents; Preface; Part I. Background: 1. A whirlwind tour of network science; 2. Network data across fields; 3. Data ethics; 4. Primer; Part II. Applications, Tools and Tasks: 5. The life-cycle of a network study; 6. Gathering data; 7. Extracting networks from data - the 'upstream task'; 8. Implementation: storing and manipulating network data; 9. Incorporating node and edge attributes; 10. Awful errors and how to amend them; 11. Explore and explain: statistics for network data; 12. Understanding network structure and organization; 13. Visualizing networks; 14. Summarizing and comparing networks; 15. Dynamics and dynamic networks; 16. Machine learning; Interlude - Good practices for scientific computing; 17. Research record-keeping; 18. Data provenance; 19. Reproducible and reliable code; 20. Helpful tools; Part III. Fundamentals: 21. Networks demand network thinking: the friendship paradox; 22. Network models; 23. Statistical models and inference; 24. Uncertainty quantification and error analysis; 25. Ghost in the matrix: spectral methods for networks; 26. Embedding and machine learning; 27. Big data and scalability; Conclusion; Bibliography; Index.
SynopsisDrawing examples from real-world networks, this essential book traces the methods behind network analysis and equips you with a toolbox of diverse methods and data modelling approaches. Suitable for both graduate students and researchers across a range of disciplines, this novel text provides a fast-track to network data expertise., 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.
LC Classification NumberTK5105.5.B3 2024

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