Social and Economic Networks

BAN434 Social and Economic Networks

Spring 2023

Autumn 2023
  • 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;


    • Can visualize, describe and compare networks;


    • Can use main network models and main models of network formation;   


    • Can analyze processes in networks (analyze how network structures affect networked societies) and understand which network structures are likely to emerge;   


    • Have developed practical skills of network analysis in R programming language;


    • Can analyze real world networks.



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

  • Teaching

    Plenary lectures, possibly guest lectures.

  • Recommended prerequisites

    A basic knowledge of mathematics (standard concepts from calculus, 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

  • Credit reduction due to overlap


  • Compulsory Activity

    One obligatory assignment is required for taking the final exam.

  • Assessment

    4 hour written individual home exam. The exam will be in English.

  • Grading Scale

    A - F

  • Computer tools

    The course will use R, 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:

    There can be recommendations on further reading (not relevant to the exam).


ECTS Credits
Teaching language


Course responsible

Professor Roman Kozlov, Department of Business and Management Science