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Course 2018-2019 a.y.

20462 - SOCIAL AND ECONOMIC NETWORKS

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  |  12 credits SECS-S/01) - EMIT (6 credits - II sem. - OP  |  SECS-S/01) - GIO (6 credits - II sem. - OP  |  SECS-S/01)
Course Director:
FERNANDO VEGA-REDONDO

Classes: 31 (II sem.)
Instructors:
Class 31: FERNANDO VEGA-REDONDO


Lezioni della classe erogate in presenza

Prerequisites

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.


Mission & Content Summary
MISSION

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 shall also illustrate matters with examples from real-world social networks. Throughout, our main concern is to develop a formal and systematic manner of understanding how social structure (i.e. the pattern of connections) affect social behavior.

CONTENT SUMMARY
  1. Graphs: definitions and measures – basic concepts: degree, distance, component, clustering, betweenness, etc.
  2. Types of networks: lattice, tree/hierarchic, random, etc.
  3. Some real-world examples: a glimpse into its wide diversity.
  4. Forces/mechanisms at work: 
    • Distance/geography.
    • Popularity.
    • Link strength and intermediation.
    • The social environment: homophily and socialization.
    • Positive and negative relationships: structural balance.
  5. Diffusion, learning, and seach in networks:
    • Epidemics: contagion processes in a large social networks.
    • Behavioral dynamics: frequency-dependent diffusion.
    • Learning in social networks: de Groot model.
    • Searching and routing in large social networks.
    • Web-filtering and search in large information networks.
  6. Networks and games:  
    • Traffic and congestion.
    • Matching and markets.
    • Bargaining and power.
    • Public goods.
    • Cooperation.
    • Coordination.

Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
  • Be familiar with the basic tools and concepts of network theory.
  • Be competent in applying game theoretic reasoning to the study of networks and network phenomena.
  • Understand, from a network perspective, important non-strategic phenomena such as search, contagion, diffusion, or learning.
  • Understand, from a network perspective, important strategic phenomenacongestion, matching and trade, power and bargaining, public goods, cooperation, or coordination.
APPLYING KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
  • Apply the knowledge outlined above to the analysis and understanding of a multitude of social and network phenomena in our hyper-connected world.

Teaching methods
  • Face-to-face lectures
  • Exercises (exercises, database, software etc.)
  • Individual assignments
  • Interactive class activities (role playing, business game, simulation, online forum, instant polls)
DETAILS

Exercises are distributed and solved in practice classes taught by a teaching assistant. These classes are very interactive, using computer methods to represent and study a wide variety of networks.


Assessment methods
  Continuous assessment Partial exams General exam
  • Written individual exam (traditional/online)
  •     x
  • Individual assignment (report, exercise, presentation, project work etc.)
  •     x
    ATTENDING AND NOT ATTENDING STUDENTS

    The exam is worth 70% of the grade and the problem sets 30%. This applies to both attending and non-attending students.


    Teaching materials
    ATTENDING AND NOT ATTENDING STUDENTS
    • The main textbook is: D. EASLEY, J. KLEINBERG, Networks, Crowds, and Markets, Cambridge University Press, 2010. Pre-print copy available at  http://www.cs.cornell.edu/home/kleinber/networks-book/
    • For a more technical coverage of some of the topics, the following two auxiliary bookscan be used:
      • F. VEGA-REDONDO, Complex Social Networks, Cambridge University Press, 2007.
      • M. JACKSON, Social and Economic Networks, Princeton University Press, 2008.
    Last change 10/06/2018 10:19