COURSE SYLLABUS

SOCIAL NETWORK ANALYSIS

1	Course Title:	SOCIAL NETWORK ANALYSIS
2	Course Code:	EKO5107
3	Type of Course:	Optional
4	Level of Course:	Second Cycle
5	Year of Study:	1
6	Semester:	1
7	ECTS Credits Allocated:	4
8	Theoretical (hour/week):	2
9	Practice (hour/week) :	0
10	Laboratory (hour/week) :	0
11	Prerequisites:	None
12	Recommended optional programme components:	None
13	Language:	Turkish
14	Mode of Delivery:	Face to face
15	Course Coordinator:	Doç. Dr. SELİM TÜZÜNTÜRK
16	Course Lecturers:	Doç. Dr. Selim TÜZÜNTÜRK
17	Contactinformation of the Course Coordinator:	Doç. Dr. Selim TÜZÜNTÜRK E-Posta: selimtuzunturk@uludag.edu.tr Telefon: 224 2941152 Adres: Bursa Uludağ Üniversitesi İktisadi ve İdari Bilimler Fakültesi,Ekonometri Bölümü,Görükle,Bursa
18	Website:
19	Objective of the Course:	The objective of this course is to teach the theory and real world applications related to social network analysis.
20	Contribution of the Course to Professional Development	The course gives students the ability to examine and analyze the social structure (social networks) we live in from a different methodological perspective.

Learning Outcomes:

1	To be able to comprehend basic concepts of Network science ;
2	To be able to comprehend theoretical framework of network science ;
3	To be able to use theoretical models of network science ;
4	To be able to make various numerical calculations by learning structural properties of networks ;
5	To be able to draw networks and to interpret their visual images ;
6	To be able to comprehend social networks and social network science ;
7	To be able to prepare social network analysis survey. To be able to collect social network data. ;
8	To be able to perform social network analysis;

22	Course Content:

Week	Theoretical	Practical
1	Definition of a network, adjacency matrix and visual representations of networks
2	Network science, it’s significance and aim
3	The history of network science
4	Structural properties of networks (geodesic distance, degree and degree distribution, clustering coefficient)
5	Introduction to theoretical models of network science
6	Random networks
7	Small world networks
8	Scale free and scale free networks
9	Social networks, social network science, social network analysis
10	History of social network analysis
11	Applications of social network analysis in social sciences
12	Network variable, data collection methods and ethics
13	Drawing of graphics
14	Calculation of statistics and metrics

23	Textbooks, References and/or Other Materials:	1.Necmi GÜRSAKAL, Sosyal Ağ Analizi Pajek Ucinet ve Gmine Uygulamalı, Dora Yayıncılık, 2009, Bursa. 2.Gürsakal, N., Aydın, Z. B., Gürsakal, S. ve Tüzüntürk, S., “Ağ Bilimi ve İstatistik”, 9. Ulusal Ekonometri ve İstatistik Sempozyumu, Dokuz Eylül Üniversitesi, İzmir, Kuşadası 28-30 Mayıs 2008, s.87. 3.WASSERMAN Stanley – Katherine FAUST, Social Network Analysis: Methods and Applications, Cambridge University Press, New York, 2008. 4.SCOTT John, Social Network Analysis: A Handbook, Sage Publications Ltd., London, 2004. 5.KOLACZYK Eric D., Statistical Analysis of Network Data: Methods and Models, Springer, New York, 2009. 6.KNOKE David – Song YANG, Social Network Analysis, Sage Publications, Inc., California, 2008. 7.DE NOOY Wouter – Andrej MRVAR – Vladimir BATAGELJ, Exploratory Social Network Analysis with Pajek, Cambridge University Press, New York, 2007. 8.CROSS Rob – Andrew PARKER, The Hidden Power of Social Networks: Understanding How Really Gets Done in Organizations, Harvard Business School Press, Boston, 2004. 9.BARABÁSI Albert László, Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life, Penguin Group, New York, 2003.
24	Assesment

TERM LEARNING ACTIVITIES	NUMBER	PERCENT
Midterm Exam	0	0
Quiz	0	0
Homeworks, Performances	0	0
Final Exam	1	100
Total	1	100
Contribution of Term (Year) Learning Activities to Success Grade		0
Contribution of Final Exam to Success Grade		100
Total		100
Measurement and Evaluation Techniques Used in the Course	In addition to the assigned assignments, the success of the student is evaluated with the classic final exam.
Information	This course is evaluated with an absolute evaluation system.

ECTS / WORK LOAD TABLE

CONTRIBUTION OF LEARNING OUTCOMES TO PROGRAMME QUALIFICATIONS

LO: Learning Objectives

PQ: Program Qualifications

Contribution Level:

1 Very Low

2 Low

3 Medium

4 High

5 Very High