Network Analytics for Marketing and Business

(fall semester lecture)

"Complexity is a sign of intelligence. Simplicity is a sign of wisdom"

Med Jones


The goal of the course is to provide Master students an introduction into applied network science to diverse topics in different fields: marketing, management, economics and informatics. This course is grounded first grounded in theory and strongly applied towards practice. Students will learn how to use available tools for collecting, visualising, analysing and interpreting network data. The course mainly deals with different kind of data: consumer networks, intra-organisational and inter-organisational networks. For students who are interested in quantitative methods, this seminar will provide an overview and the basic understandings of the main research methodologies associated with network science in the aforementioned areas. Topics typically falling under this umbrella include: social structure, social influence, contagion, diffusion, social capital, or collective action.


  • Prof. Dr Claudio J. Tessone
  • Dr Manuel S. Mariani


Target Audience:
Master students assigned to “Wahlpflichtbereich" BWL 4

Each fall semester

Practical understanding, application, interpretation and documentation of network science methods.


Fundamental courses in statistics (e.g. Empirical Methods MOEC0021). R programming skills (or the willingness to develop this knowledge PRIOR to the seminar) are a necessary requirement. Students who are proficient with other programming languages (e.g. Python) can also participate and do the exercise in it. The required skills are on par with the contents of e.g. the following online classes: coursera and datamind as well as codeschool.

Solving the exercises assigned in class (40%); developing and presenting the final project (60%).

Dates and Location:
Tuesdays, 18.09 - 11.12.2018
14:00 - 18:00
Location: BIN-1-D-25

Further information:

Network Science
Market Research

Don’t forget to officially register yourself using the registration tools at the University of Zurich.

Download Syllabus (PDF, 330 KB)


Slides of the lectures:
18.09: Kick-off. (PDF, 11 MB)

18.09: L01: Introduction to Network Theory. (PDF, 4 MB)