Master 2020/2021

Social Networks

Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'

Category 'Best Course for New Knowledge and Skills'

Type: Elective course (Digital Humanities)

Area of studies: Fundamental and Applied Linguistics

Delivered by: School of Linguistics

Where: Faculty of Humanities

When: 2 year, 1, 2 module

Mode of studies: offline

Instructors: Сорокин Семен Александрович

Master’s programme: Цифровые методы в гуманитарных науках

Language: English

ECTS credits: 3

Contact hours: 32

Course Syllabus

Abstract

The course "Social Networks" introduces students to the new interdisciplinary field of research. Emerged in sociology, the theory of social networks in recent years, has attracted considerable interest of economists, mathematicians, physicists, experts in data analysis, computer engineers. Initially, researches focused on the study of social networks, i.e. sets of links connecting the social actors in accordance with their interaction. Nowadays, the study of actors’ relations includes economic, financial, transport, computer, language and many other networks. The course examines the methods of analyzing the structure of networks, model of their emergence and development, and the processes occurring in networks.

Learning Objectives

• Цель освоения дисциплины — познакомить с методом сетевого анализа и теорией графов, научить пользоваться сетевым анализом для исследования культурных явления и объектов культуры.

Expected Learning Outcomes

• Know the basic principles of network analysis
• Know the advantages and disadvantages of various network analytic tools and methods
• Know the major network modeling programs
• Be able to explore the advantages and disadvantages of various network analytic tools and methods
• Be able to correctly selects appropriate model / method of network analysis for a given problem
• • To provide students with an understanding of the basic principles of network analysis and lay the foundation for future learning in the area.
• • To explore the advantages and disadvantages of various network analytic tools and methods, and demonstrate how they relate to other methods of analysis.
• • To develop student familiarity, through hands-on experience, with the major network modeling pro-grams, so that they can use them and interpret their output.

Course Contents

• Position Analysis in Social Networks
  Centrality and Influence. Measures of Centrality. Two-mode networks: transformation, graphical repre-sentation, and analysis. Centrality and two-mode networks in the studies of power and influence.
• Personal Ties and Social Support
  Network measures for dyads and triads. The forbidden triad. Clustering. Identifying tightly connected groups and subgroups in social networks. Small-world phenomenon. Homophily principal in personal rela-tionships. Cultural and historical differences in network connectivity. Personal ties and social support.
• SNA methodology III
  Centrality and Influence. Measures of Centrality. Two-mode networks: transformation, graphical representation, and analysis. Centrality and twomode networks in the studies of power and influence.
• Network Data, Matrices, Graphic Representation of Social Networks, and Basic Network Measures
  Survey instruments for collecting network data. Network data collection and ethical issues. Basic measures of network characteristics. Graphic representation of network relations.
• SNA methodology I
  Survey instruments for collecting network data. Network data collection and ethical issues. Basic measures of network characteristics. Graphic representation of network relations.
• SNA methodology II
  Network measures for dyads and triads. Identifying tightly connected groups and subgroups in social networks. Small-world phenomenon. Homophily principal in personal relationships. Cultural and historical differences in network connectivity. Personal ties and social support.
• Introduction
  Social network analysis: Methods or theory? Structural approach. Interdisciplinary interest in network analysis. Network theories most popular in social sciences. Key network concepts: network, structure, nodes, ties, sociogram, structural and compositional variables, etc. Types of network data. Sampling and data collection in network analysis.

Assessment Elements

• Исследовательский проект 1
• Исследовательский проект 2

Interim Assessment

• Interim assessment (2 module)
  0.5 * Исследовательский проект 1 + 0.5 * Исследовательский проект 2

Bibliography

Recommended Core Bibliography

• Carrington, P. J., Scott, J., & Wasserman, S. (2005). Models and Methods in Social Network Analysis. Cambridge: Cambridge University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=132264

Recommended Additional Bibliography

• Newman, M. (2010). Networks: An Introduction. Oxford University Press, 2010