Professur für Soziologie, insb. Digitale Sozialwissenschaft
Public Lecture: Stochastic Network Modeling - Enhancing Interpretation and Facilitating Comparisons
30. September 2026
Foto: UHH/Esfandiari
A public lecture on stochastic network modeling will be hosted by the Professorship for Sociology, with a focus on Digital Social Science at the University of Hamburg, together with colleagues from the Statistical Methods group in the Department of Sociology at the University of Groningen.
Date: Monday, 26 October 2026
Time: 10:00-12:00 (welcome from 09:30; informal get-together 12:00-13:00)
Location: University of Hamburg; room to be announced
The event is aimed at researchers, students, and practitioners with an interest in social network analysis and the stochastic modeling and statistical analysis of social networks and related relational processes.
With a focus on generative stochastic network models, the lecture will introduce approaches such as Exponential Random Graph Models (ERGMs) and Stochastic Actor-Oriented Models (SAOMs). It will then discuss how effects in these models can be interpreted and compared across datasets and model specifications, including recent developments based on probability-scale marginal effects and meta-analytic approaches.
The programme features:
- A general introduction to stochastic network modeling by Christian Steglich (University of Groningen).
- A discussion of interpreting and comparing network effects by Daniel Gotthardt (University of Hamburg) and Marijtje van Duijn (University of Groningen).
Empirical examples will include friendship networks among pupils and organizational networks.
Participation is free. The exact room will be announced on the event page. For the current programme, registration information, and updates on the location, please visit:
This event is part of COMMODE (Comparing Effects in Stochastic Network Models), a joint initiative of the Department of Sociology at the University of Groningen and the Faculty of Business, Economics and Social Sciences at the University of Hamburg, funded through the Groningen-Hamburg Fund. COMMODE aims to improve how effects in stochastic network models are defined, compared, and communicated, and to foster further research cooperation between method developers and applied researchers.
