Магистратура
2020/2021
Прикладные методы сетевого анализа
Статус:
Курс обязательный (Прикладная политология)
Направление:
41.04.04. Политология
Кто читает:
Департамент социологии
Где читается:
Факультет социальных наук
Когда читается:
2-й курс, 1, 2 модуль
Формат изучения:
без онлайн-курса
Преподаватели:
Зайцев Дмитрий Геннадьевич
Прогр. обучения:
Прикладная политология
Язык:
русский
Кредиты:
7
Контактные часы:
56
Программа дисциплины
Аннотация
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.
Цель освоения дисциплины
- 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
Планируемые результаты обучения
- 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
- Be able to confidently use available data to test proposed network hypotheses
- Be able to develop a solid network theoretical foundation for the project at hand
- 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 expresses network research ideas in English in written and oral communication
- Have the skills to effectively presents network research ideas to peers, instructors, and general audience
Содержание учебной дисциплины
- IntroductionSocial 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.
- SNA methodology ISurvey instruments for collecting network data. Network data collection and ethical issues. Basic measures of network characteristics. Graphic representation of network relations.
- SNA methodology IINetwork 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.
- SNA methodology IIICentrality and Influence. Measures of Centrality. Two-mode networks: transformation, graphical representation, and analysis. Centrality and twomode networks in the studies of power and influence.
- SNA models IThe strength of weak ties. Social capital. Structural holes. Examples of social network analysis in political science. Political networks. Policy networks. Networks in International Relations.
- SNA models IIBlockmodeling and clustering. Cluster analysis on networks. Principal component analysis
- SNA models IIISocial influence model. Social selection model. Exponential random graph models (ERGM).
- ConclusionThis session will bring all approaches to social network analysis together and apply it to the students’ current projects.
Элементы контроля
- Final Research Project
- Homework Assignments (5 x Varied points)
- In-Class Labs (9-10 x Varied points)
- Quizzes (Best 9 of 10, Varied points)
- Final Research Project
- Homework Assignments (5 x Varied points)
- In-Class Labs (9-10 x Varied points)
- Quizzes (Best 9 of 10, Varied points)
Промежуточная аттестация
- Промежуточная аттестация (2 модуль)0.5 * Final Research Project + 0.2 * Homework Assignments (5 x Varied points) + 0.2 * In-Class Labs (9-10 x Varied points) + 0.1 * Quizzes (Best 9 of 10, Varied points)
Список литературы
Рекомендуемая основная литература
- 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
Рекомендуемая дополнительная литература
- Newman, M. (2010). Networks: An Introduction. Oxford University Press, 2010