Bachelor 2024/2025

Introduction to Network Analysis

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

Category 'Best Course for New Knowledge and Skills'

Type: Elective course (Sociology)

Area of studies: Sociology

Delivered by: School of Sociology

Where: Faculty of Social Sciences

When: 4 year, 3 module

Mode of studies: offline

Open to: students of all HSE University campuses

Instructors: Daria Maltseva

Language: English

ECTS credits: 6

Course Syllabus

Abstract

This course is an introductory course in network analysis, designed to familiarize graduate students with the general concepts and basic techniques of network analysis in sociological re-search, gain general knowledge of major theoretical concepts and methodological techniques used in social network analysis, and get some hands-on experience of collecting, analyzing, and mapping network data with SNA software. In addition, this course will provide ample opportu-nities to include network concepts in students’ master theses work.

Learning Objectives

• The goal of the course is ensure that students understand topics and principles of network analsis.

Expected Learning Outcomes

• Be able to confidently uses available data to test proposed network hypotheses.
• Be able to correctly selects appropriate model / method of network analysis for a given problem.
• Be able to develop a solid network theoretical foundation for the project at hand.
• Be able to explore the advantages and disadvantages of various network analytic tools and methods.
• Be able to integrate network information found from various sources and compensate for lack of data by adjusting models.
• Be able to master advanced research methods, including network methods, without direct supervision, and is capable of using these methods to analyze complex models.
• Have the skill to processe learned information, and integrate learned material into a cohesive research toolchest.
• Have the skills to effectively presents network research ideas to peers, instructors, and general audience.
• Have the skills to expresses network research ideas in English in written and oral communication.
• Know the advantages and disadvantages of various network analytic tools and methods.
• Know the basic principles of network analysis.
• Know the major network modeling programs.

Course Contents

• 1. Introduction
• 2. Network Data
• 3. Macro level: Network statistics
• 4. Micro level: Centralities
• 5. Mezo level: Cohesive subgroups
• 6. Network clustering
• 7. Blockmodeling

Assessment Elements

• Final project
  (in groups of up to 3 people)
• Assignments at the seminar - each seminar (7)
• 1 presentation with the report
  (in groups up to 3 people)

Interim Assessment

• 2024/2025 3rd module
  0.2 * 1 presentation with the report + 0.3 * Assignments at the seminar - each seminar (7) + 0.5 * Final project

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
• Luke, D. A. (2015). A User’s Guide to Network Analysis in R. Cham: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1114415
• Nooy, W. de, Mrvar, A., & Batagelj, V. (2005). Exploratory Social Network Analysis with Pajek. New York: Cambridge University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=138973

Recommended Additional Bibliography

• Lazega, E., & Snijders, T. A. B. (2016). Multilevel Network Analysis for the Social Sciences : Theory, Methods and Applications. Cham: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1119294
• Newman, M. (2010). Networks: An Introduction. Oxford University Press, 2010

Authors

• MALTSEVA Daria VASILEVNA
• DESIATOVA MARIIA IVANOVNA