Offers an overview of the analytic methods and conceptual perspectives of a social network approach to social science and humanities research. Using the R statistical computing language, covers techniques for collecting, formatting, and visualizing network data, as well as tools for calculating the mathematical properties of social networks, such as centrality, clustering, transitivity, and structural equivalence. Introduces statistical methods for social network analysis, such as exponential random graph models and stochastic actor-oriented models.