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Магистерская программа «Прикладная статистика с методами сетевого анализа»

Introduction to Network Analysis

2021/2022
Учебный год
ENG
Обучение ведется на английском языке
4
Кредиты
Статус:
Курс обязательный
Когда читается:
1-й курс, 1, 2 модуль

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

Learning Objectives

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

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

Course Contents

  • Introduction
  • SNA methodology
  • SNA methodology II
  • SNA methodology III
  • SNA models I
  • SNA models II
  • Conclusion
Assessment Elements

Assessment Elements

  • non-blocking Final Research Project
  • non-blocking Homework Assignments (5 x Varied points)
  • non-blocking In-Class Labs (9-10 x Varied points)
  • non-blocking Quizzes (Best 9 of 10, Varied points)
Interim Assessment

Interim Assessment

  • 2021/2022 1st module
  • 2021/2022 2nd module
    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)
Bibliography

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
  • Kolaczyk E. D., Csárdi G. Statistical analysis of network data with R. – New York : Springer, 2014. – 207 pp.
  • 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

  • Kadry, S., & Al-Taie, M. Z. (2014). Social Network Analysis : An Introduction with an Extensive Implementation to a Large-scale Online Network Using Pajek. Oak Park, IL: Bentham Science Publishers. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=694016
  • 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