Statistical models for social network analysis

This course aims to provide an introduction to popular statistical methods for social network analysis and to enable participants to use these in their own research.

Ziele und Nutzen

Course language

English

Course topic

Statistical models for social networks have become widely used in social science research in the past decades. This course aims to provide an introduction to popular statistical methods for social network analysis and to enable participants to use these in their own research. Following a general introduction to network modelling and some key methods (e. g, MRQAP, ERGM), the course will focus on studying network dynamics using Stochastic Actor-oriented Models (SAOMs). The course will demonstrate how the covered methods can be flexibly applied across different social settings to answer a wide range of research questions.

Course objectives

By the end of the course, participants will be able to:

• discuss why network data requires different statistical methods to be analysed than non-network (‹individual›) data
• intuitively understand popular statistical methods for analysing social networks, such as the MRQAP, ERGM, and SAOM
• apply these methods on empirical data using R

Course methods / Learning activities

The course is delivered as a combination of short lectures, practical demonstrations, and individual exercises. Each method will first be presented through examples and basic principles. This will be followed by a developed example application in R that will be presented by the lecturer. Finally, participants will get the opportunity to try out and/or practice each method on their own, using either the examples provided or their own dataset.

Prerequisites

The course will focus on developing practical skills and intuition, with pointers for those who wish to dig deeper in statistical/computational details. Because of this, the course can be useful for anyone with the following background:

• some familiarity with the R programming language
• basic knowledge of social network analysis concepts and descriptive methods
• applied understanding of the ideas behind statistical testing and regression models

Remarks

Participants are welcome to bring their own data and research questions to the workshop. There will be opportunity to work on these, ask questions, and troubleshoot models.

Dieses Angebot hat keine Wahl- und Anschlussmöglichkeiten.

Mi, 3.6.2026, 8.45–16.30 Uhr
Do, 4.6.2026, 8.45–16.30 Uhr
Fr, 5.6.2026, 8.45–16.30 Uhr

Campus Brugg-Windisch

Dr András Vörös, Associate Professor (School of Social Policy and Society, University of Birmingham)

• Dozierende an Hochschulen
• Mitarbeitende an Hochschulen

• Grundkenntnisse in der Programmiersprache R
• Grundkenntnisse in Konzepten und beschreibenden Methoden der sozialen Netzwerkanalyse
• Angewandtes Verständnis der Ideen hinter statistischen Tests und Regressionsmodellen

CHF 400

Alle Informationen als PDF

Die vollständigen Informationen zu diesem Angebot sind auch als druckbares PDF verfügbar.

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Dr. Jasmin Näpfli
+41 56 202 79 54
jasmin.naepfli@fhnw.ch

Zu diesem Angebot gibt es keine Info-Anlässe.