This article discusses the stochastic actor-oriented model for analyzing panel data of
networks. The model is defined as a continuous-time Markov chain, observed at two or more …

Statistical models for social networks as dependent variables must represent the typical
network dependencies between tie variables such as reciprocity, homophily, transitivity, etc …

It is hard to avoid seeing ethnicity, race, or nationality wherever one looks. Differences in
education, income, and health are often patterned along ethnic or racial lines. But how do …

Social insects make elaborate use of simple mechanisms to achieve seemingly complex
behavior and may thus provide a unique resource to discover the basic cognitive elements …

Graph theory is a valuable framework to study the organization of functional and anatomical
connections in the brain. Its use for comparing network topologies, however, is not without …

Networks and network analysis are arguably one of the largest growth areas of the early
twenty-first century in the quantitative sciences. Despite roots in social network analysis …

Networks are ubiquitous in science and have become a focal point for discussion in
everyday life. Formal statistical models for the analysis of network data have emerged as a …

This article provides an introductory summary to the formulation and application of
exponential random graph models for social networks. The possible ties among nodes of a …

Nearly a century of empirical research examines how neighborhood properties influence a
host of phenomena such as crime, poverty, health, civic engagement, immigration, and …

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 …