Бакалавриат
2026/2027
Введение в сетевой анализ
ID 1111415
Статус:
Курс по выбору (Социология)
Кто читает:
Департамент социологии
Где читается:
Факультет социальных наук
Когда читается:
4-й курс, 3 модуль
Охват аудитории:
для всех кампусов НИУ ВШЭ
Язык:
английский
Кредиты:
4
Контактные часы:
30
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
- Introduction
- SNA methodology
- SNA methodology II
- SNA methodology III
- SNA models I
- SNA models II
- Conclusion
- 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
- Homework
- Final projectВыполняется индивидуально
- Assignments at the seminar - each seminar (7)
Interim Assessment
- 2026/2027 3rd module0.3 * Homework + 0.3 * Assignments at the seminar - each seminar (7) + 0.4 * Final project
Bibliography
Recommended Core Bibliography
- Exploratory social network analysis with Pajek, Nooy de, W., 2018
- Models and methods in social network analysis, , 2006
Recommended Additional Bibliography
- Raj P. M. K., Mohan A., Srinivasa K.G. (2018) Basics of Graph Theory. In: Practical Social Network Analysis with Python. Computer Communications and Networks. Springer, Cham. Retrieved from https://link.springer.com/chapter/10.1007%2F978-3-319-96746-2_1#citeas
- Social network analysis, Scott, J., 2017