Course outline

The table below contains an approximate outline for our activities in this module. For the last meeting, we will see if there are participants who want to present a solo/group project as their exam work (and if so, they will give us a talk), or I would prepare some materials on topics not yet covered in the course.

date/topic	lecture	seminar
3.11.2025 or 11.11.2025 Introduction	The metaphor and theory behind the set of methods. Basic definitions: nodes and edges, directed and undirected ties, weighted ties. Micro / meso / macro levels of analysis. Triads & exchange theory (briefly). A very short history of network analysis. Examples from the range of disciplines (e.g., history, political sciences, etc.). Examples of more interest for management students.	Ways to collect network data (secondary data, questionnaires, etc.). Software overview (beyond R). A very short intro to web-scraping. Data organization: matrix and edgelist. Loading data to R.
10.11.2025 or 18.18.2025 Centrality measures and network positions	Overview of the centrality measures. Degree centrality vs. betweennesss centrality. Problems with the most common centrality measures. Brokerage and Burt’s constraint. Weak ties and – good ideas, job search, etc.	Practical session: from data loading to metrics’ computation. We will work with a number of networks from various contexts (educational, corporate, criminal, and so on) to check if the observed measures of centrality are universal and to learn how to choose them correctly. Finally, we will take the network measures to run simple regression models.
17.11.2025 or 25.11.2025 Topology and network structures	Network descriptive statistics: number of ties/nodes, diameter, shortest paths, etc. Density, reciprocity, clustering coefficient. Homophily. Community detection algorithms (briefly). Core/periphery strcture. “Small world” networks. Cultural and organizational consequences of different structures.	Network visualizaions (R and other softwares: Gephi, Pajek, Cosmograph, etc.) and how to use them properly in storytelling. Computing network measures. Community detecton practice. Testing the empirical network structure against network compositions discussed in class.
24.11.2025 or 2.12.2025 2-mode networks	Towards the theory of n-mode networks. Affiliation networks. Network projections and the “dual perspective”. Vizualizations and analytical tips. Dimensionality reduction techniques for 2-mode data. Examples from the American corporate elite and the company’s interlocking.	Workshop on 2-mode networks. During this class, we will go through the typical workflow for the 2-mode networks and revise the previous topics (e.g., apply the community detection algorithms to the network projections or find the most important nodes in one of them).
1.12.2025 or 9.12.2025 Structural equivalence	Classical structuralist approaches to network analysis and why do we need them. Positions, blocks, roles. Network structures and blockmodeling.	Practical session on blockmodeling. We will learn these techniques by looking at networks of different relations among the company employees. We will also discuss why we might need multiple types of relations when doing social network analysis.
8.12.2025 or 16.12.2025 Course overview and new directions	Course participants may suggest the topics they are interested in for this class. My suggestions are temporal networks and/or ERGM. We can also consider a particular phenomenon (job search, corporate interlocking, etc.) or concept (negative ties, 2-mode networks, etc.) in more details.	TBA