Social and Economic Networks

BAN434 Social and Economic Networks

Autumn 2020

Spring 2021
  • Topics

    Networks are important in shaping behavior in many environments. For example, economic production and supply chains are organized as networks, new technologies diffuse in the economy through research and development collaboration networks. Social networks pervade our social and economic lives. They play a central role in the transmission of information about job opportunities and are critical to the trade of many goods and services. The presence of networks makes it important to understand which network structures can emerge and how networks impact behavior.

    The course offers an introduction to networks and applications of social and economic networks. The goal of the course is to provide students with the theoretical foundations of network theory and help them understand behavior and outcomes in networked societies.

    The course contains

    • an overview of social and economic networks as well as empirical observations about network structure;
    • description of network models and models of network formation;
    • models of how network structures impact behavior: diffusion, learning,  games on networks, and networked markets;
    • practical examples of network applications;
    • methods of networks visualization. 

  • Learning outcome


    Students obtain essential knowledge of network analysis applicable to real world data.    



    After completion of the course the students can

    • Use basic notation and terminology used in network science;
    • Visualize, describe and compare networks;
    • Use main network models and main models of network formation;   
    • Analyze processes in networks (analyze how network structures affect networked societies) and understand which network structures are likely to emerge;   
    • Develop practical skills of network analysis in R programming language;
    • Analyze real work networks.



    • Learn new methods of network analysis and apply them to real work networks.

  • Teaching

    Plenary lectures, possibly guest lectures.

  • Recommended prerequisites

    A basic knowledge of mathematics (standard concepts from linear algebra, probability and statistic, which correspond to MET1 Mathematics for economists and MET2 Statistics for economists)

    A basic programming experience (preferably in R)

  • Required prerequisites

    No special requirements

  • Requirements for course approval




    One obligatory assignment is required for taking the final exam.

  • Assessment




    4 hour school exam. The exam will be in English.

  • Grading Scale

    A - F

  • Computer tools

    The course will use R (Python and special programs can also be used), which is open source. Details regarding the installation of different packages and additional tools will be provided.  

  • Literature

    Course textbook:

    Matthew O. Jackson (2008) Social and Economic Networks, Princeton University Press.


    Suggested readings:



ECTS Credits
Teaching language

Spring. Offered first time Spring 2021.

Please note: Due to the present corona situation, please expect parts of this course description to be changed before the autumn semester starts. Particularly, but not exclusively, this relates to teaching methods, mandatory requirements and assessment.

Course responsible

Professor Roman Kozlov, Department of Business and Management Science