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Member rate 2,713.79 zł
Non-Member rate 5,427.58 zł
Save 221.03 zł Loyalty discount applied automatically*
Save 5% on each additional course booked
* If you attended a qualifying previous Methods School in 2025 or 2026, you qualify for 221.03 zł off your course fee.
Online: 3 – 4 September, 09:00 – 12:30 CEST
Jagiellonian University: 8 – 11 September
The abundance of network metaphors and new relational data signify how exciting the field of social network analysis is for political research. This course offers you an introduction to the fundamentals of social network analysis in an interactive online teaching environment.
In the sessions, we will cover central concepts in the network literature and discuss how these concepts are theoretically motivated, methodologically operationalised, and applied. In-class exercises and package tutorials equip you with the skills and hands-on experience required to manage and analyse network data using R. Through the course, you will learn: key network concepts and terminology; strategies for collecting, visualising, and analysing network data; a range of measures and models for answering theoretically-informed questions; and examples of their application to political science as well as examples for you to apply.
This course is designed to bring you to an intermediate level of understanding, with an overview of more advanced options to support further exploration in the field.
James Hollway is Co-Director of the Global Governance Centre, Head of the Environment and Sustainability Specialisation, and Associate Professor of International Relations/Political Science at the Graduate Institute of International and Development Studies in Geneva. His research develops multilevel and dynamic network theories, methods, and data for studying institutionalised cooperation and conflict on trade, health, and environmental issues such as fisheries and freshwater. His work has been published with Cambridge University Press, Journal of Conflict Resolution, International Studies Quarterly, Global Environmental Politics, International Environmental Agreements, Policy Studies Journal, Sociological Theory, Sociological Methodology, Social Networks, and Network Science.
This course consists of two main sections. The first three days we set the foundations for describing and analysing social networks, or “network analysis”. The last two days builds on this by exploring how we can explain network structures or other aspects of socio¬political life and investigate relational mechanisms using networks, or “network modelling”.
This session introduces the theoretical assumptions and key terminology of network analysis. We discuss what relations mean, how to collect network data, and the implications of design choices such as the boundary or type of network data to collect.
This session covers methods for measuring nodes centrality and embeddedness, as well as network measures such as how centralised the network is as a whole. We discuss when to use different types of centrality and cohesion measures, and discuss the implications of network multimodality on these measures.
This session investigates networks’ meso scale. We explore the identification and emergence of groups or communities within networks, and identify and discuss the roles that nodes or ties may have in or between those groups. This session will introduce blockmodeling.
This session reviews several ideal typical network macro-structures or topologies and how they are created or generated. We then move to discussing models of diffusion and learning on networks, in particular the operation of threshold and compartment models upon networks that allow more complex models of diffusion to be explored.
Formation and Change This session provides an overview of the bestiary of network models used to explain how networks are formed or change, including multiple regression quadratic assignment procedures, exponential random graph models, stochastic actor-oriented models, and relational event models such as the dynamic network actor model. Throughout the course, participants will work with fun fictional or real-world data, and are encouraged to apply the methods to their own research interests.
The course is structured into five live sessions, each lasting 3 hours. The first two sessions will take place online on Thursday 3 – Friday 4 September. The remaining two sessions will take place at Jagiellonian University on Tuesday 8 – Thursday 10 September. You must attend all sessions to complete the course.
The instructor will also conduct Q&A sessions and offer designated office hours for one-to-one consultations.
This is an introductory course to social and political network analysis, including practical exercises/tutorials to provide hands-on experience. As such, familiarity with R and basic statistical methods, including linear and logistic regression, is required. While we will occasionally consider mathematical formulae, knowledge of linear or matrix algebra is not required.
The practical exercises will make use of the stocnet suite of R packages for network analysis and modelling. Installing the ‘migraph’ package from CRAN will install all required packages, and make the tutorials available. In addition to the 15 hours of teaching (hybrid/in-person sessions), participants should expect to spend up to 2 hours reading and up to 2 hours completing the tutorials or reviewing the material covered in class before/after each session.
The course description is subject to adaptations (e.g. taking into account new developments in the field, participant demands, group size, etc.).
You will engage in a variety of activities designed to deepen your understanding of the subject matter. While the cornerstone of your training experience will be daily live teaching sessions, the learning commitment will extend beyond these. This ensures that you engage deeply with the course material, participate actively, and complete assessments to solidify your learning.
If you have registered and paid for the course, you will be given access to our Learning Management System (LMS) approximately two weeks before the course start date. Here, you can view course materials such as pre-course readings.
During the course week, participants are expected to commit time to preparing for each session, including readings and practical assignments.
By registering for this course, you confirm that you possess the knowledge required to follow it. The instructor will not teach these prerequisite items. If in doubt, please contact us before registering.