2023/2024
Введение в сетевой анализ
Лучший по критерию «Полезность курса для Вашей будущей карьеры»
Лучший по критерию «Полезность курса для расширения кругозора и разностороннего развития»
Лучший по критерию «Новизна полученных знаний»
Статус:
Маго-лего
Когда читается:
2 модуль
Охват аудитории:
для своего кампуса
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 sociological research, 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 opportunities to include network concepts in students’ master theses work.
Learning Objectives
- To introduce students to the fundamental concepts, terminology, and theoretical foundations of social network analysis — the network approach to social phenomena, basic structural notions (nodes, ties, types of networks), and core theories such as homophily, weak ties, and structural holes.
- To develop students' ability to think about social questions in network terms — to represent data as networks, distinguish levels of analysis (ego, dyad, group, whole network), and choose and correctly interpret basic network measures (centrality, density, cohesion, community detection).
- To develop basic practical skills for analyzing and visualizing networks using specialized software (e.g., Gephi, igraph, NetworkX, Pajek), computing key metrics on real datasets and interpreting the results.
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 to social network analysis
- Network Analysis as a Method
- Foundational Network Measures
- Community Detection and Blockmodeling
- Social Influence Models
- Social Selection Models
- SNA software
Bibliography
Recommended Core Bibliography
- Doing social network research : network-based research design for social scientists, Robins, G., 2015
Recommended Additional Bibliography
- 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, Batagelj, V., & Mrvar, A. (2011). Exploratory Social Network Analysis with Pajek: Vol. Rev. and expanded 2nd ed. Cambridge University Press.