A User’s Guide to Network Analysis in R, 1st ed. 2015 Use R! Series

Presenting a comprehensive resource for the mastery of network analysis in R, the goal of Network Analysis with R is to introduce modern network analysis techniques in R to social, physical, and health scientists. The mathematical foundations of network analysis are emphasized in an accessible way and readers are guided through the basic steps of network studies: network conceptualization, data collection and management, network description, visualization, and building and testing statistical models of networks. As with all of the books in the Use R! series, each chapter contains extensive R code and detailed visualizations of datasets. Appendices will describe the R network packages and the datasets used in the book. An R package developed specifically for the book, available to readers on GitHub, contains relevant code and real-world network datasets as well.

Douglas Luke is Professor and Director of the Center for Public Health Systems Science at the George Warren Brown School of Social Work at Washington University in St. Louis. He is a leading researcher in the fields of health policy, and his work focuses on the evaluation, dissemination, and implementation of evidence-based public health policies. Dr. Luke has worked extensively with systems science methodologies, especially the analysis of social networks with regards to the implementation of public health policies. He is a member of the Institute for Public Health, a founding member of the Washington University Network of Dissemination and Implementation Researchers (WUNDIR), and serves on the Interagency Committee on Smoking and Health at the U.S. Department of Health and Human Services.

Provides a practical, hands-on tour of the major network analytic tasks R is capable of, including network data management, network visualization, network description, and network modeling Includes all R code needed for examples used throughout the book Serves as an excellent reference resource for teaching and learning network science, analytics, and techniques Includes supplementary material: sn.pub/extras