Social Network Analysis Labs in R and SoNIA

McFarland, Daniel A., Solomon Messing, Michael Nowak and Sean J. Westwood.

To run the following labs install R (Linux, MacOS X or Windows) and execute the following command in R (this will download and install all needed packages and data):

source("http://sna.stanford.edu/setup.R")

Chapters

1. “Introductory Lab.” Nowak, Michael and Daniel A. McFarland. 2010.

2. “Methodological Beginnings – Basic Triadic and Cohesion Measures.” Nowak, Michael and Daniel A. McFarland. 2010.

3. “Clusters, Factions and Cores.” Nowak, Michael and Daniel A. McFarland. 

4. “Centralities and Their Interrelation.” Sukumaran, Abhay,Michael Nowak and Daniel A. McFarland.

5. "Affiliation Data and Network Mobility." Messing, Solomon and Daniel A. McFarland. 2010.

6. "Structural Equivalences and Block-Modeling." Nowak, Michael, Solomon Messing, Sean J. Westwood and Daniel A. McFarland. 2010.

7. “Peer Influence and QAP Regression." Messing, Solomon, Sean J. Westwood and Daniel A. McFarland. 2010.

8. "Exponential-Family Random Graph Models.” Westwood, Sean J. and Daniel A. McFarland. 2010.

9. "Converting igraph to SoNIA with R." Westwood, Sean J. and Daniel A. McFarland. 2010.

10. "rSoNIA and Visualizing Social Network Dynamics." Bender-deMoll, Skye and Daniel A. McFarland. 2010.

Additional software

SoNIA is a Java-based package for visualizing dynamic or longitudinal "network" data. (This is a temporary download meant to fix SoNIA while a new release is under development.)

Software required to run SoNIA:

Acknowledgements: Special thanks to Skye Bender-deMoll and James Moody. An earlier version of the introductory lab, the Exponential Random Graph Model lab, and rSoNIA lab were developed in collaboration with them. We have revised, extended and reorganized the content of those labs here.

This material is based upon work supported by the Office of the President at Stanford University and the National Science Foundation under Grants No. 0835614 and 0624134. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of Stanford University or the National Science Foundation.