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Social Network Analysis with Siena
Five-day Course • June 17 - 21, 2013• Lawrence, Kansas
Presented by the Quantitative Training Program of Psychology and the Center for Research Methods and Data Analysis at the University of Kansas.
Institute Overview
Longitudinal Social Network Analysis with the SIENA software package. With a longitudinal focus, the course will emphasize the actor-based approach to social network analysis including how to model network predictors, covariates, and change.
This is a one-week course designed primarily for researchers who are currently doing longitudinal social network research or who are embarking upon it. More specifically, the course is about how to analyze panel data on complete social networks; "complete" meaning that the collection of all network ties within one or several groups is being studied, "panel"; that it is observed at two or more discrete moments in time. The course will treat statistical modelling of network dynamics according to the stochastic actor-based approach (Snijders 2001, 2005; Snijders, Steglich and Schweinberger, 2007). The course will use the computer program SIENA and will consist of a mixture of classroom teaching and hands-on computer work. Some attention will be paid also to non-longitudinal network models, the so-called Exponential Random Graph Models.
Instructors
Christian Steglich studied Mathematics and Computer Sciences at the TU Berlin, followed by a doctoral study at the Interuniversity Center for Social Science Theory and Methodology (ICS) in Groningen / The Netherlands. Since his PhD on framing effects in individual decision making (2003), he has been part of the team developing the SIENA software for longitudinal social network analysis and exponential random graph modelling, and has been teaching workshops on the use of SIENA since 2004. Currently, he is employed as associate researcher at the Faculty of Behavioural and Social Sciences at the University of Groningen. His current research activities are embedded in the European Collaborative Research Project “Dynamics of Networks and Actors across Levels”, funded under the ESF EUROCORES scheme (NWO grant 461-05-960), and the project “Social Network Analysis of Peers and Smoking in Adolescence”, funded by the Medical Research Council of the United Kingdom.
Software and Computer Support
Participants are expected to bring their own laptops, on which SIENA can be installed before or during the course. It is expected that participants have a basic knowledge of statistical modeling. No specific prior knowledge of network analysis, or of the SIENA program, is assumed. However, attendees who know nothing about social network analysis are advised to read some introductory material as mentioned below in the reference list. Further information and publications about this method and software can be found at http://stat.gamma.rug.nl/siena.html
R (http://www.r-project.org/) is also recommended
Syllabus
Social Network Analysis with Siena
Christian Steglich
University of Groningen
| Monday | Introduction to dynamic network modeling |
| 9:00 – 10:30 | An introduction to stochastic actor-oriented models for network dynamics |
| 10:45 –12:00 | Introduction to SIENA |
| 12:00 – 1:15 | Lunch * |
| 1:15 – 2:30 | Examples of applications |
| 2:45 – 5:00 | Computer work with Siena |
| 5:00 – 8:30 | Free BBQ (burgers, veggie burgers, brats) and open beer/wine bar at Holiday Inn |
| Tuesday | Continued dynamic network modeling; Modeling of networks and behavior |
| 9:00 – 10:30 | The basic estimation algorithm. Parameter interpretation |
| 10:45 – 12:00 | Model specification; Special topics: composition change, structurally determined values, missing values |
| 12:00 – 1:30 | Lunch * |
| 1:30 – 3:00 | Introduction to co-evolution of networks and behavior |
| 2:15 – 3:30 | Estimation |
| 3:15 – 5:00 | Computer work with Siena: co-evolution of networks and behavior |
| 5:45 | Free Bus to Downtown Departs |
| 8:45 | Free Bus returns from Downtown |
| Wednesday | Examples and further background |
| 9:00 – 10:30 | Diverse examples |
| 10:45 – 12:00 | Continuation of computer work with SIENA |
| 12:00 – 1:15 | Lunch * |
| 1:15 – 3:00 | Model specification. Goodness of fit tests |
| 3:15 – 5:00 | Simulation with Siena |
| 5:45 | Free Bus to Downtown Departs |
| 8:45 | Free Bus returns from Downtown |
| Thursday | Exponential random graph models; Multilevel dynamic network analysis |
| 9:00 – 10:30 | Non-longitudinal network models: Exponential Random Graph Models (ERGMs) |
| 10:45 – 12:00 | Continuation of ERGMs, computer work with pnet or statnet |
| 12:00 – 1:30 | Lunch * |
| 1:30 – 3:00 | Meta-analysis of dynamic network analysis results |
| 3:15 – 5:00 | Computer work with Siena: running Siena through batch files |
| 5:45 | Free Bus to Downtown Departs |
| 8:45 | Free Bus returns from Downtown |
| Friday | Communication of results; New developments |
| 9:00 – 10:30 | Communication of results to a wider audience |
| 10:45 – 12:00 | Last question time |
| 12:00 – 1:30 | Lunch * |
| 1:00 – 5:00 | Individual Consultation on data analysis projects |
* Our group lunch is included in the Holiday Inn room rate and tickets for the group lunch are also available for purchase for those not staying at the Holiday Inn. There are other lunch options in Lawrence as well.
Literature
Those who are new to the field of network analysis are advised to have a look at one (or both) of the two general introductory texts on social network analysis mentioned below, to get a general impression of this encompassing domain. Those who like to do some introductory reading more specifically on the topic of this course are advised to read Snijders, van de Bunt & Steglich (2009) as a non-technical introduction to modeling network dynamics. Further references and the software can be found at http://stat.gamma.rug.nl/siena.html
This literature list is not final, and will be updated for the course. Introductory literature, social network analysis
The free online introductory textbook on social network analysis (2005), Introduction to social network methods, by Robert Hanneman and Mark Riddle. http://faculty.ucr.edu/~hanneman/nettext/
John Scott, Social Network Analysis: A Handbook. 2nd edition. Sage, 2000.
Stochastic actor-based models for network dynamics
Snijders, Tom A.B., The statistical evaluation of social network dynamics. M.E. Sobel and M.P. Becker (eds.), Sociological Methodology-2001, 361-395. Boston and London: Basil Blackwell. (This is a general technical exposition of the method for modeling network dynamics.)
Snijders, Tom A.B. Models for Longitudinal Network Data. Chapter 11 in P. Carrington, J. Scott, & S. Wasserman (Eds.), Models and Methods in Social Network Analysis. New York: Cambridge University Press (2005), p. 215-247. (This is another general, rather technical exposition of the method for modeling network dynamics, presumably written in a somewhat more accessible style than the preceding article.)
Snijders, T. A. B., Steglich, C., & Schweinberger, M. Modeling the co-evolution of networks and behavior. In K. van Montfort, H. Oud & A. Satorra (Eds.), Longitudinal models in the behavioral and related sciences, p. 41-71. Mahwah, NJ: Lawrence Erlbaum (2007). (This is a general technical exposition of the method for modeling the interdependent dynamics of networks and behavior.)
Snijders, Tom A.B., Christian E.G. Steglich, Michael Schweinberger, and Mark Huisman. (2007). Manual for SIENA version 3. Groningen: University of Groningen, ICS. Oxford: University of Oxford, Department of Statistics. http://www.stats.ox.ac.uk/~snijders/siena/sie_man31.pdf
Snijders, T.A.B., Steglich, C.E.G., and van de Bunt, G.G. (2009). Introduction to actor-based models for network dynamics. Submitted for publication. http://www.stats.ox.ac.uk/~snijders/siena/SnijdersSteglichVdBunt2008.pdf (This is a general non-technical introduction to the methods for modeling network dynamics as well as for modeling the interdependent dynamics of networks and behavior, and has been accepted for publication in Social Networks.)
Steglich, Christian E.G., Snijders, Tom A.B. and Pearson, Michael. (2009). Dynamic Networks and Behavior: Separating Selection from Influence. Submitted for publication. http://www.stats.ox.ac.uk/~snijders/siena/SteglichSnijdersPearson2009.pdf (This is a general exposition of the method for modeling the interdependent dynamics of networks and behavior, with many connections to other social science research on this topic.)
Course Files
Below are links to course files for those who enrolled in the course. The files are password protected to respect the intellectual property rights of the instructors. By using your login information you agree not to share your login information or the content protected by it.
Coming soon.
Contact Information
For information on course content, contact Christian Steglich.
A full list of prices and fellowship opportunities for this course and all the courses offered at this year's Summer Institutes in Statistics can be found on the Fees and Registration Page.