This book brings together recent advances and presents a comprehensive picture of the scientific study of networks. It includes discussion of computer networks, social networks, biological networks, and others, and an introduction to the mathematics of network theory, including analysis techniques, computer algorithms, and network modeling.
This book brings together recent advances and presents a comprehensive picture of the scientific study of networks. It includes discussion of computer networks, social networks, biological networks, and others, and an introduction to the mathematics of network theory, including analysis techniques, computer algorithms, and network modeling.
Mark Newman received a D.Phil. in physics from the University of Oxford in 1991 and conducted postdoctoral research at Cornell University before joining the staff of the Santa Fe Institute, a think-tank in New Mexico devoted to the study of complex systems. In 2002 he left Santa Fe for the University of Michigan, where he is currently Anatol Rapoport Distinguished University Professor of Physics and a professor in the university's Center for the Study of Complex Systems.
Inhaltsangabe
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
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
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