Cambridge: Cambridge University Press, 2024. - 506 p. - ISBN 1107174007.
Complex networks are key to describing the connected nature of the society that we live in. This book, the
second of two volumes, describes the
local structure of random graph models for
real-world networks and determines when these models have a giant component and when they are
small-, and ultra-small, worlds. This is the first book to cover the theory and implications of
local convergence, a crucial technique in the analysis of sparse random graphs. Suitable as a resource for
researchers and PhD-level courses, it uses examples of real-world networks, such as the
Internet and citation networks, as motivation for the models that are discussed, and includes exercises at the end of each chapter to develop intuition. The book closes with an extensive discussion of related models and problems that demonstrate modern approaches to network theory, such as
community structure and directed models.
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