Course 2017-2018 a.y.



Department of Decision Sciences

Course taught in English

Go to class group/s: 31
CLMG (6 credits - II sem. - OP  |  SECS-S/01) - M (6 credits - II sem. - OP  |  SECS-S/01) - IM (6 credits - II sem. - OP  |  SECS-S/01) - MM (6 credits - II sem. - OP  |  SECS-S/01) - AFC (6 credits - II sem. - OP  |  SECS-S/01) - CLEFIN-FINANCE (6 credits - II sem. - OP  |  SECS-S/01) - CLELI (6 credits - II sem. - OP  |  SECS-S/01) - ACME (6 credits - II sem. - OP  |  SECS-S/01) - DES-ESS (6 credits - II sem. - OP  |  SECS-S/01) - EMIT (6 credits - II sem. - OP  |  SECS-S/01) - GIO (6 credits - II sem. - OP  |  SECS-S/01)
Course Director:

Classes: 31 (II sem.)

Course Objectives

The course presents the main theoretical developments of the modern field of social networks, as these have been applied to understand some of the most important social and economic phenomena that are central to our highly connected societies.
The emphasis of the course is on the theory, but we also illustrate matters with examples from real - world social networks.
Initially, we focus on phenomena such as search, contagion, diffusion, or learning, which can be largely conceived as non-strategic. Then, we turn to the study of strategic problems such as congestion, trade, intermediation, power, or bargaining, which display an essential strategic component and thus have to be analyzed using the tools of Game Theory.
Throughout, our main concern is to develop a formal and systematic manner of understanding how social structure (i.e. the pattern of connections) affect a wide variety of social behavior.

Course Content Summary

  • Graphs: definitions and measures - basic concepts: degree, distance, component, clustering, betweenness, etc.
  • Types of networks: lattice, tree/hierarchic, random,etc.
  • Some real-world examples: a glimpse into its wide diversity.
  • Force /mechanisms at work.
    • Distance / geography.
    • Popularity.
    • Link strength and intermediation.
    • the social environment: homophily and socialization.
    • Positive and negative relationships: structural balance.
  • Diffusion and search in networks.
    • Epidemics: contagion processes in a large social nerworks.
    • Behavioral dynamics: frequency-dependent diffusion.
    • Decentralized search in a small world: walking the web.
    • Learing in networks: de Groot model.
  • Information networks: the World Wide Web ( WWW ).
    • Structure of the WWW.
    • Web-filtering: centralized search engines & semantic webs.
  • Networks and games: traffic, markets, learning and power.
    • Traffic and congestion in networks.
    • Matching and markets.
    • Intermediation in markets.
    • Bargaining and power in networks.

Detailed Description of Assessment Methods

The final grade of the course is based on the following :

  • Regularly assigned problem sets (30%);
  • Final exams (70%).
The course requires regular attendance, since exercises and assignments are an integral part of it. Therefore, it does not contemplate the possibility of “non-attending students”.


  • D. Easley, J. Kleinberg, Networks, Crowds, and Markets, Cambridge University Press, 2010, (Pre-­print copy available at:­book/).
For a more technical coverage of some of the topics, the following two auxiliary books
can be used:
  • F. VEGA-REDONDO, Complex Social Networks, Cambridge University Press, 2007.
  • M. JACKSON, Social and Economic Networks, Princeton University Press, 2008.
Exam textbooks & Online Articles (check availability at the Library)


Given the theoretical nature of the course, the student is supposed to have a good background in basic mathematics and a familiarity with logical/mathematical reasoning. In particular, knowledge of the following tools at an intermediate level is presumed
  • Calculus and algebra.
  • Dynamical systems.
  • Game Theory.
Last change 23/06/2017 10:10