Course Information


Course Information
Course Title Code Semester L+U Hour Credits ECTS
SOCIAL NETWORK ANALYSIS 803400815051 3 + 0 3.0 10.0

Prerequisites None

Language of Instruction English
Course Level Graduate Degree
Course Type Elective
Mode of delivery
Course Coordinator
Instructors
Assistants
Goals In this course, it is aimed to explore fundamentals and applications of social network analysis (SNA), for revealing information existing in a network involving people.
Course Content "The topics of the course will cover introduction to SNA, software for analysis and visualization, subgroup analysis, balance theory, two mode networks, connection and distance, bridges and brokerage, dynamic network analysis, review of topics and literature, prestige and popularity, ranking and structural prestige, citations, equivalence and blockmodelling. "
Learning Outcomes 1) Knows the principles, techniques, methods and applications related to social network analysis.
2) Sosyal ağ analizi tekniklerini uygulayabilir.
3) Can use social network analysis tools.

Weekly Topics (Content)
Week Topics Teaching and Learning Methods and Techniques Study Materials
1. Week Introduction to SNA Lecture

 Homework
2. Week Software for analysis and visualization Lecture

 Homework
3. Week Subgroup analysis Lecture

 Homework
4. Week Balance Theory Lecture

 Homework
5. Week Two mode networks Lecture

 Homework
6. Week Connection and distance Lecture

 Homework
7. Week Bridges and brokerage Lecture

 Homework
8. Week Dynamic network analysis Lecture

 Homework
9. Week Review of topics and literature Lecture

 Homework
10. Week Review of topics and literature Lecture

 Homework
11. Week Prestige and popularity Lecture

 Homework
12. Week Ranking and structural prestige Lecture

 Homework
13. Week Citations Lecture

 Homework
14. Week Equivalence and blockmodelling Lecture

 Homework

Sources Used in This Course
Recommended Sources
De Nooy, W., Mrvar, A., & Batagelj, V. (2018). Exploratory social network analysis with Pajek: Revised and expanded edition for updated software (Vol. 46). Cambridge University Press.
Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications (Vol. 8). Cambridge university press.

Relations with Education Attainment Program Course Competencies
Program RequirementsContribution LevelDK1DK2DK3
PY15555
PY55555
PY65555

*DK = Course's Contrubution.
0 1 2 3 4 5
Level of contribution None Very Low Low Fair High Very High
.

ECTS credits and course workload
Event Quantity Duration (Hour) Total Workload (Hour)
Course Duration (Total weeks*Hours per week) 14 3
Work Hour outside Classroom (Preparation, strengthening) 14 9
Homework 2 20
Presentation (Including Preparation Time) 1 20
Project (Including Preparation and presentation Time) 1 1
Report (Including Preparation and presentation Time) 1 1
Activity (Web Search, Library Work, Trip, Observation, Interview etc.) 1 5
Practice (Teaching Practice, Music/Musical Instrument Practice , Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice) 1 1
Seminar 1 1
Time to prepare for Quiz 1 10
Midterm Exam 1 1
Time to prepare for Midterm Exam 1 20
Final Exam 1 1
Time to prepare for Final Exam 1 40
Total Workload
Total Workload / 30 (s)
ECTS Credit of the Course
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Course Information
  • Course Information
  • Weekly Topics (Content)
  • Sources Used in This Course
  • Relations with Education Attainment Program Course Competencies
  • ECTS credits and course workload