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Regular version of the site
Master 2018/2019

Social and Economic Networks: Models and Analysis

Type: Elective course (Modern Social Analysis)
Area of studies: Sociology
When: 1 year, 3, 4 module
Mode of studies: distance learning
Master’s programme: Modern Social Analysis
Language: English
ECTS credits: 3
Contact hours: 4

Course Syllabus

Abstract

The course gives empirical background on social and economic networks, and an overview of concepts used to describe and measure networks. It describes models of networks formation, including random network models as well as strategic formation models, and some hybrids. The course discusses a series of models of how networks impact behavior, including contagion, diffusion, learning, and peer in uences. The course is based on the online course «Social and Economic Networks: Models and Analysis» (https://www.coursera.org/learn/social-economic-networks)
Learning Objectives

Learning Objectives

  • Overview of concepts used to describe and measure networks
  • Get empirical background on social and economic networks
  • Discuss a series of models of how networks impact behavior, including contagion, diffusion, learning, and peer in uences
Expected Learning Outcomes

Expected Learning Outcomes

  • Understanding basic concepts of social network analysis
  • Understanding how the networks form (network models)
  • Understanding how networks can contribute to the explanation of specific social, political, economic and cultural phenomena
  • Understanding network approach to analysing social behavior
  • Mastering basic skills of working with SNA software Gephi and Pajek
Course Contents

Course Contents

  • Introduction, Background and Definitions. Basic terminology and network examples
    Background and Definitions. Basic terminology and network examples
  • Network metrics. Centrality Measures: Degree, Betweenness, Closeness, Eigenvector, and Katz-Bonacich.
    Centrality Measures. Degree, Betweenness, Closeness, Eigenvector, and Katz-Bonacich.
  • Network models: Exponential Random Graph Models, Growing Random Networks, Preferential Attachment and Power Laws
    Exponential Random Graph Models, Growing Random Networks, Preferential Attachment and Power Laws
  • Strategic Network Formation: , The Connections Model, Directed Networks, Hybrid Models of Choice and Chance.
    The Connections Model, Directed Networks, Hybrid Models of Choice and Chance.
  • Diffusion on Networks: Empirical Background, Random Network Models of Contagion, The SIS model, Fitting a Simulated Model to Data.
    Empirical Background, Random Network Models of Contagion, The SIS model, Fitting a Simulated Model to Data.
  • Learning on Networks: Bayesian Learning on Networks, The DeGroot Model of Learning on a Network, Convergence of Beliefs, The Wisdom of Crowds, How Inuence depends on Network Position
    Bayesian Learning on Networks, The DeGroot Model of Learning on a Network, Convergence of Beliefs, The Wisdom of Crowds, How Inuence depends on Network Position
  • Games on Networks - Peer Effects: Network Games, Peer Influences: Strategic Complements and Substitutes, the Relation between Network Structure and Behavior
    Peer Effects: Network Games, Peer Influences: Strategic Complements and Substitutes, the Relation between Network Structure and Behavior
Assessment Elements

Assessment Elements

  • non-blocking Online tests
    MOOC (online tests)
  • non-blocking In-class Participation
    Сlassroom discussions face-to face; work in small groups
Interim Assessment

Interim Assessment

  • Interim assessment (4 module)
    0.3 * In-class Participation + 0.7 * Online tests
Bibliography

Bibliography

Recommended Core Bibliography

  • Huber, L. M., & Schneider, H. L. (2008). Social Networks : Development, Evaluation and Influence. New York: Nova Science Publishers, Inc. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=311265
  • Newman, M. E. J. (2010). Networks : An Introduction. Oxford: OUP Oxford. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=nlebk&AN=458550

Recommended Additional Bibliography

  • Easley, D., & Kleinberg, J. (2010). Networks, Crowds, and Markets : Reasoning About a Highly Connected World. New York: Cambridge eText. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=324125