FSS:MEBn5034 Social Network Analysis in R - Course Information

MEBn5034 Social Network Analysis in R

Extent and Intensity

1/1/0. 6 credit(s). Type of Completion: z (credit).

Teacher(s)

Mgr. Lukáš Lehotský, Ph.D. (lecturer)
doc. Mgr. Petr Ocelík, Ph.D. (lecturer)

Guaranteed by

doc. PhDr. Břetislav Dančák, Ph.D.
Department of International Relations and European Studies – Faculty of Social Studies
Contact Person: Olga Cídlová, DiS.
Supplier department: Department of International Relations and European Studies – Faculty of Social Studies

Timetable

Wed 14:00–15:40 M117

Prerequisites (in Czech)

! MEB434 Social Network Analysis in R && !NOW( MEB434 Social Network Analysis in R )

Course Enrolment Limitations

The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 3/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20

fields of study / plans the course is directly associated with

• Energy Security Studies (Eng.) (programme FSS, N-MS)
• Energy Policy Studies (programme FSS, N-EPS) (2)
• Environmental Studies (programme FSS, N-HE)
• European Politics (Eng.) (programme FSS, N-PL)
• European Studies (programme FSS, N-EVS) (2)
• European Studies (programme FSS, N-MS)
• Environmental Humanities (programme FSS, N-HE3)
• Conflict and Democracy Studies (Eng.) (programme FSS, N-PL)
• International Relations and Energy Security (programme FSS, N-MS)
• International Relations and Energy Security (programme FSS, N-MVEB) (2)
• International Relations (programme FSS, N-MS)
• International Relations (programme FSS, N-MV) (2)

Course objectives

The course introduces students to (meta)theoretical assumptions and methodological apparatus of social network analysis. Each class consists of a lecture which introduces theoretical background and “mechanics” of a given concept or method, and a workshop where students use this knowledge through practical tasks.

Learning outcomes

Upon successful completion of the course, students will be able to set-up SNA-defined research design, specify appropriate techniques and rigorously use them. The emphasis will be put on the practical use of this knowledge.

Syllabus

• Organizational session / R modular architecture, data import
• Objects in R
• Data manipulation 1
• Data manipulation 2
• Introduction to SNA: main assumptions and concepts
• Relational data: notations, matrices, and diagrams
• Network topology: connectedness, distances, and motifs
• Centrality: degree, closeness, betweenness
• Centralization: degree, closeness, betweenness
• Cohesive subgroups: triadic census, cliques, and communities
• Research design and data collection
• Data visualization
• Exploratory SNA
• Inferential SNA

Literature

• ROBINS, Garry. Doing social network research : network-based research design for social scientists. First published. Los Angeles: Sage, 2015, xiv, 261. ISBN 9781446276136. info
• BORGATTI, Stephen P., Martin G. EVERETT and Jeffrey C. JOHNSON. Analyzing social networks. Thousand Oaks, Calif.: Sage, 2013, viii, 296. ISBN 9781446247419. info
• ADLER, Joseph. R in a nutshell. 2nd ed. Sebastopol, CA: O'Reilly, 2012, xix, 699. ISBN 9781449312084. info

Teaching methods

lectures, workshops, readings, assignments

Assessment methods

assignments grading

Language of instruction

English

Further Comments

Study Materials
The course is taught annually.

• Enrolment Statistics (Autumn 2022, recent)
  
• Permalink: https://is.muni.cz/course/fss/autumn2022/MEBn5034