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Networks

By: Newman, MarkMaterial type: TextTextLanguage: English Publication details: India: Oxford University Press, 2018. Edition: 2nd edDescription: xi, 780pISBN: 9780198839972Subject(s): System analysis | Network analysis (Planning) | Systems biology | Engineering systems | Social systems | Mathematical and Statistical Physics | Computational Physics | Information science | Biological networks | Computer scienceDDC classification: 004.7
Contents:
Table of Contents 1. Introduction Part I: The empirical study of networks 2. Technological networks 3. Networks of information 4. Social networks 5. Biological networks Part II: Fundamentals of network theory 6. Mathematics of networks 7. Measures and metrics 8. Computer algorithms 9. Network statistics and measurement error 10. The structure of real-world networks Part III: Network models 11. Random graphs 12. The configuration model 13. Models of network formation Part IV: Applications 14. Community structure 15. Percolation and network resilience 16. Epidemics on networks 17. Dynamical systems on networks 18. Network search
Summary: The study of networks, including computer networks, social networks, and biological networks, has attracted enormous interest in the last few years. The rise of the Internet and the wide availability of inexpensive computers have made it possible to gather and analyze network data on an unprecedented scale, and the development of new theoretical tools has allowed us to extract knowledge from networks of many different kinds. The study of networks is broadly interdisciplinary and central developments have occurred in many fields, including mathematics, physics, computer and information sciences, biology, and the social sciences. This book brings together the most important breakthroughs in each of these fields and presents them in a coherent fashion, highlighting the strong interconnections between work in different areas. Topics covered include the measurement of networks; methods for analyzing network data, including methods developed in physics, statistics, and sociology; fundamentals of graph theory; computer algorithms; mathematical models of networks, including random graph models and generative models; and theories of dynamical processes taking place on networks.
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Item type Current library Call number Status Date due Barcode
Book Book NISER LIBRARY
004.7 NEW-N (Browse shelf(Opens below)) Checked out to Aryan Pandharinath Neel (2111228) 28/05/2024 24951

Table of Contents
1. Introduction
Part I: The empirical study of networks
2. Technological networks
3. Networks of information
4. Social networks
5. Biological networks
Part II: Fundamentals of network theory
6. Mathematics of networks
7. Measures and metrics
8. Computer algorithms
9. Network statistics and measurement error
10. The structure of real-world networks
Part III: Network models
11. Random graphs
12. The configuration model
13. Models of network formation
Part IV: Applications
14. Community structure
15. Percolation and network resilience
16. Epidemics on networks
17. Dynamical systems on networks
18. Network search

The study of networks, including computer networks, social networks, and biological networks, has attracted enormous interest in the last few years. The rise of the Internet and the wide availability of inexpensive computers have made it possible to gather and analyze network data on an unprecedented scale, and the development of new theoretical tools has allowed us to extract knowledge from networks of many different kinds. The study of networks is broadly interdisciplinary and central developments have occurred in many fields, including mathematics, physics, computer and information sciences, biology, and the social sciences. This book brings together the most important breakthroughs in each of these fields and presents them in a coherent fashion, highlighting the strong interconnections between work in different areas.

Topics covered include the measurement of networks; methods for analyzing network data, including methods developed in physics, statistics, and sociology; fundamentals of graph theory; computer algorithms; mathematical models of networks, including random graph models and generative models; and theories of dynamical processes taking place on networks.

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