The combination of the compactness of networks, featuring small diameters, and their
complex architectures results in a variety of critical effects dramatically different from those in …

From the Internet to networks of friendship, disease transmission, and even terrorism, the
concept--and the reality--of networks has come to pervade modern society. But what exactly …

The most promising class of statistical models for expressing structural properties of social
networks observed at one moment in time is the class of exponential random graph models …

We study the family of network models derived by requiring the expected properties of a
graph ensemble to match a given set of measurements of a real-world network, while …

We offer a solution to a long-standing problem in the theory of networks, the creation of a
plausible, solvable model of a network that displays clustering or transitivity—the propensity …

This book provides a concise modern introduction to the science of complex networks. The
book is based on lectures for university students and non-specialists. The aim is to introduce …

Stochastic blockmodels are generative network models where the vertices are separated
into discrete groups, and the probability of an edge existing between two vertices is …

Exponential random graph models (ERGMs) are powerful tools for formulating theoretical
models of network generation or learning the properties of empirical networks. They can be …

We study spatial embeddings of random graphs in which nodes are randomly distributed in
geographical space. We let the edge probability between any two nodes to be dependent on …

The expansion of construction land due to urbanization is the most rapid land use change in
contemporary human history and has always occupied high-quality cropland, posing a …