12th Winter School and Master Class on Longitudinal Social Network Analysis

the art network
© BarabásiLab (A.-L. Barabási, S.P. Fraiberger, A. Grishchenko, M. Resch, C. Riedl, und R. Sinatra)

12th Winter School and Master Class on Longitudinal Social Network Analysis takes place 8-11th February, 2022.

The combined event is organised at the Institute for Analytical Sociology by Christian Steglich, Anastasia Menshikova and Madelene Töpfer. The event is to be held fully online. 

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The Winter School will consist of an alternation of lectures, Q&A sessions, and practical work on assignments. The Master Class will consist of an in-depth discussion of submitted papers, and consultations devoted to the analysis of participants’ data sets.

It is assumed that the participants have a good basic understanding of statistical methods, including in particular logistic regression; a good understanding of the basics of social network analysis (e.g., the textbook by Borgatti, Everett, and Johnson); and a good working knowledge of R. We have prepared a separate page with preparation material, which you can access here.



The course will take place via zoom; the zoom address will be distributed to registered participants on Monday 7 February 2022 in the morning hours.

Course Material

The course material will be available at this shared drive location (please click here). It will be updated throughout the course week, so be careful to update material that you may have downloaded, and be careful with printing.






About schedule

The following is a rough outline of how the course topics will be distributed over the week. Afternoon sessions are shorter.

There will be longer breaks of 30 minutes between sessions and short breaks around each full and each half hour within sessions and much opportunity for asking questions. 

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Winter School, February 8-10

The Winter School introduces participants to the analysis of longitudinal, group-centered network data by way of stochastic, actor-based models (Snijders, van de Bunt & Steglich, 2010), and to the analysis of peer influence processes taking place in such dynamically changing networks (Steglich, Snijders & Pearson, 2010). The objective of the Winter School is that course participants develop an understanding of the models, familiarise themselves with the use of the RSiena software for model estimation, and learn how to tell a good model specification from a bad one. The Winter School will be taught by Christian Steglich with the support of Anastasia Menshikova. This is the second time (after 2017) the Winter School will take place in Norrköping. Previous editions took place at the University of Groningen (2005-2015, 2019) ETH Zürich (2016), and online (2021).

Master Class, February 11

The Master Class on Longitudinal Social Network Analysis is an extra day of deepening your experience with longitudinal network modelling. There are two ways how you can make use of this opportunity. On the one hand, we reservetime forconsultations about getting your data analysis started, if you bring own data with you and have not yet started analyzing it. On the other hand, it is possible todiscuss your work in progress. If you have already started analyzing your data, this is an opportunity to get expert feedback on your preliminary work. Invited discussant will be Tom Snijders and (depending on paper content) maybe others; they might “zoom in” for participating.

The procedure for the Master Class is the following. Participants that would like to actively participate should submit an abstract in which they explain their analysis (or analysis plans)This abstract should be handed in together with the main application for the Winter School. Within one week after the application deadline, authors will be informed about acceptance for the Master Class. For accepted preliminary work, we ask you to submit papers of no more than 12 pages, accompanied by an R-script and (if possible) data, to enable reproducibility of the analysis, by January 21. Participation in the Master Class is optional. If you do not wish to participate in the consultations or paper discussions actively, you can still join the Master Class event as a listener and contribute to the discussions.

Prerequisites and Preparation

Prerequisites for participation are familiarity with basic social network analysis, some knowledge of intermediate statistics, and basic familiarity with the R statistical software environment. We expect the participants to bring their own laptops and install the required software beforehand


We especially invite researchers who are in the process of collecting or analysing their own longitudinal data sets to participate in the Master Class. For participants without own data, several sample data sets will be made available. 


If you have questions regarding the contents of the classes, please, address them to Christian Stieglich. The questions regarding the application procedure and the event should be sent to Anastasia Menshikova. Madelene Topfer will be available to discuss payments.


For an overview of earlier Winter Schools on Longitudinal Social Network Analysis, click here

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