{"product_id":"working-with-network-data-a-data-science-perspective-hardback-9781009212595","title":"Working with Network Data; A Data Science Perspective (Hardback) 9781009212595","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eWorking with Network Data\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003eA Data Science Perspective\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cem\u003eSuitable for students and researchers in a range of disciplines, this novel text provides a fast-track to network data expertise.\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eJames Bagrow (Author), Yong‐Yeol Ahn (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781009212595, Cambridge University Press\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 13 June 2024\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e554 pages\u003cbr\u003e25.1 x 17.7 x 3.5 cm, 1.13 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cem\u003e\u003cfont size=\"3\"\u003e'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\u003c\/font\u003e\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003eDrawing 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.\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eContents\u003cbr\u003e Preface\u003cbr\u003e Part I. Background: 1. A whirlwind tour of network science\u003cbr\u003e 2. Network data across fields\u003cbr\u003e 3. Data ethics\u003cbr\u003e 4. Primer\u003cbr\u003e Part II. Applications, Tools and Tasks: 5. The life-cycle of a network study\u003cbr\u003e 6. Gathering data\u003cbr\u003e 7. Extracting networks from data – the 'upstream task'\u003cbr\u003e 8. Implementation: storing and manipulating network data\u003cbr\u003e 9. Incorporating node and edge attributes\u003cbr\u003e 10. Awful errors and how to amend them\u003cbr\u003e 11. Explore and explain: statistics for network data\u003cbr\u003e 12. Understanding network structure and organization\u003cbr\u003e 13. Visualizing networks\u003cbr\u003e 14. Summarizing and comparing networks\u003cbr\u003e 15. Dynamics and dynamic networks\u003cbr\u003e 16. Machine learning\u003cbr\u003e Interlude – Good practices for scientific computing\u003cbr\u003e 17. Research record-keeping\u003cbr\u003e 18. Data provenance\u003cbr\u003e 19. Reproducible and reliable code\u003cbr\u003e 20. Helpful tools\u003cbr\u003e Part III. Fundamentals: 21. Networks demand network thinking: the friendship paradox\u003cbr\u003e 22. Network models\u003cbr\u003e 23. Statistical models and inference\u003cbr\u003e 24. Uncertainty quantification and error analysis\u003cbr\u003e 25. Ghost in the matrix: spectral methods for networks\u003cbr\u003e 26. Embedding and machine learning\u003cbr\u003e 27. Big data and scalability\u003cbr\u003e Conclusion\u003cbr\u003e Bibliography\u003cbr\u003e Index.\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Statistical physics [\u003ca title=\"See our other books on Statistical physics\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Statistical%20physics%20%5BPHS%5D%22\"\u003ePHS\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Cambridge University Press","offers":[{"title":"Brand New","offer_id":52501203157272,"sku":"9781009212595","price":46.56,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781009212595i.jpg?v=1786217011","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/working-with-network-data-a-data-science-perspective-hardback-9781009212595","provider":"Freshly Printed Books","version":"1.0","type":"link"}