Магистратура
2022/2023
Анализ социальных сетей
Лучший по критерию «Полезность курса для расширения кругозора и разностороннего развития»
Лучший по критерию «Новизна полученных знаний»
Статус:
Курс по выбору (Сравнительные социальные исследования / Comparative Social Research)
Направление:
39.04.01. Социология
Кто читает:
Департамент социологии
Где читается:
Факультет социальных наук
Когда читается:
1-й курс, 3 модуль
Формат изучения:
без онлайн-курса
Охват аудитории:
для своего кампуса
Преподаватели:
Семенова Анна Михайловна
Прогр. обучения:
Сравнительные социальные исследования
Язык:
английский
Кредиты:
3
Контактные часы:
40
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 political research, gain general knowledge of major theoretical concepts and methodological techniques used in social network analysis (SNA), and get some hands-on experience of collecting, analyzing, and mapping network data with SNA software. In addition, this course will provide ample opportunities to include network concepts in students’ master theses work.
Learning Objectives
- The goal of the course is to ensure that students understand topics and principles of network analysis
- The goal of the course is to ensure that students understand topics and principles of network analysis. The basics of this discipline should be used in the following courses and activities: - Master thesis writing - All other program related courses
Expected Learning Outcomes
- Be able to confidently use 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 process learned information, and integrate learned material into a cohesive research toolset
- 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 I
- SNA methodology II
- SNA methodology III
- SNA models I
- SNA models II
- SNA models III
- Conclusion
Assessment Elements
- In-Class Labs (9-10 x Varied points)
- Course Project
- Homework Assignments (5 x Varied points)
- Quizzes (Best 9 of 10, Varied points)
Interim Assessment
- 2022/2023 3rd module0.2 * In-Class Labs (9-10 x Varied points) + 0.5 * Course Project + 0.1 * Quizzes (Best 9 of 10, Varied points) + 0.2 * Homework Assignments (5 x Varied points)
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
- 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
- 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
- Newman, M. (2010). Networks: An Introduction. Oxford University Press, 2010