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).
In-person direct teaching

Teacher(s)

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

Guaranteed by

doc. Mgr. Petr Ocelík, 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 PC25

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: 11/20, 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 - double degree (programme FSS, N-EPS)
• 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 the (meta)theoretical assumptions and methodological apparatus of social network analysis. Each class consists of a lecture, which introduces the theoretical background and "mechanics" of a given concept or method, and a workshop, in which students apply this knowledge through practical tasks.

Learning outcomes

On successful completion of the course, students will be able to set up an SNA-defined research design, specify appropriate techniques and apply them rigorously. Emphasis is placed on the practical application of this knowledge.

Syllabus

• R interface and objects
• Data manipulation in R
• Data import/export in R
• Introduction to SNA: main assumptions and concepts
• Relational data: notations, matrices, and diagrams
• Network cohesion
• Centrality and centralization
• Cohesive subgroups: triadic census, cliques, and communities
• Inferential SNA: from QAP to ERGMs

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 (recent)
  
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