NETWORK ANALYSIS PROGRAMME COURSE DESCRIPTION

Code	Name of the Course Unit	Semester	In-Class Hours (T+P)	Credit	ECTS Credit
YBS410	NETWORK ANALYSIS	8	3	3	8

GENERAL INFORMATION
Language of Instruction :	Turkish
Level of the Course Unit :	BACHELOR'S DEGREE, TYY: + 6.Level, EQF-LLL: 6.Level, QF-EHEA: First Cycle
Type of the Course :	Compulsory
Mode of Delivery of the Course Unit	-
Coordinator of the Course Unit	Assist.Prof. DİDEM TETİK KÜÇÜKELÇİ
Instructor(s) of the Course Unit	Assist.Prof. HADI POURMOUSA
Course Prerequisite	No

OBJECTIVES AND CONTENTS
Objectives of the Course Unit:	The aim of the course is to focus on graph theory, understanding the concept and importance of social networks, learning the types and differences of networks, social network and community analysis, data collection for social networks, visualization of networks with the help of computers, theories and applications of network analysis.
Contents of the Course Unit:	Contents of the course include providing necessary basic information and similar structures about the subjects such as learning various algorithms and applications in network environments, network flow design, showing nodes as data structures and expressing their relations with each other, search on the network structure, shortest path algorithms, various problems of optimization techniques and their solution methods and obtaining optimal results.

KEY LEARNING OUTCOMES OF THE COURSE UNIT (On successful completion of this course unit, students/learners will or will be able to)
Explain the key concepts and algorithms of network analysis. (explain)
Analyze network structure with appropriate techniques.(analysis)
Choose the appropriate methodology for analyzing networks.(choose)
Calculate the connection between network nodes.(calculate)
Combine big data analysis and statistical analysis methods.(combine)

WEEKLY COURSE CONTENTS AND STUDY MATERIALS FOR PRELIMINARY & FURTHER STUDY
Week	Preparatory	Topics(Subjects)	Method
1	Literature Review	Introduction to Network Science, Graph Basics	Lecture, Discussion, Application
2	Literature Review	Creating Networks with Python (NetworkX Library)	Lecture, Discussion, Application
3	Literature Review	Visualizing a Network Created with Python (Matplotlib Library)	Lecture, Discussion, Application
4	Literature Review	Network Metrics	Lecture, Discussion, Application
5	Literature Review	Calculating Centrality Measures with Python	Lecture, Discussion, Application
6	Literature Review	Visualizing Centrality Measures with Python	Lecture, Discussion, Application
7	Literature Review	Calculating and Visualizing Coefficient and Efficiency Measures with Python	Lecture, Discussion, Application
8	Literature Review	Network Models	Lecture, Discussion, Application
9	Literature Review	Creating Different Network Models with Python	Lecture, Discussion, Application
10	-	MID-TERM EXAM	-
11	Literature Review	Network Datasets	Lecture, Discussion, Application
12	Literature Review	Processing Datasets with Python (Pandas Library)	Lecture, Discussion, Application
13	Literature Review	Community Analysis and In-Depth Analysis	Lecture, Discussion, Application
14	Literature Review	Community Analysis and In-Depth Analysis with Python	Lecture, Discussion, Application
15	Literature Review	General Review	Lecture, Discussion, Application
16	-	FINAL EXAM	-
17	-	FINAL EXAM	-

SOURCE MATERIALS & RECOMMENDED READING
Gursakal, N. (2009). Sosyal Ag Analizi. Dora Publications.
Tunali V. (2016). Sosyal Ag Analizi. Nobel Publications.

ASSESSMENT
Assessment & Grading of In-Term Activities	Number of Activities	Degree of Contribution (%)	Description	Examination Method
Mid-Term Exam	1	30		Computer-Lab-Practice Exam
Practice	1	20
Final Exam	1	50		Project Submission (No Examination)
TOTAL	3	100

Level of Contribution
0	1	2	3	4	5

KNOWLEDGE
Theoretical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Define concepts such as management, manager and leader.					4
2	Analyze the accuracy, reliability and validity of the new information obtained from the data.						5

KNOWLEDGE
Factual
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Report the obtained data.						5
2	Prepare software and projects related with the field.						5

SKILLS
Cognitive
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Use the appropriate resources for data analysis related with the field.						5
2	Analyze the work processes.						5

SKILLS
Practical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Manage projects as part of a team.						5
2	Apply the material, techniques and analyzes in relation with the subject for project and work flows.						5

OCCUPATIONAL
Autonomy & Responsibility
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Fulfill responsibility with a focus on result in individual and team studies.						5

OCCUPATIONAL
Learning to Learn
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Recognizes what he/she knows about his/her field or not.						5
2	Act the theoretical knowledge in real life with learning to learn approach.						5
3	Apply different methods and techniques with an innovative approach in his/her research.						5

OCCUPATIONAL
Communication & Social
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Apply the results obtained in accordance with voluntarism and social responsibility projects.						5
2	Establish a healthy contact with colleagues					4
3	Share the analyzes and obtained results with colleagues.					4
4	Cooperate with colleagues at international level with the help of foreign language competency.					4

OCCUPATIONAL
Occupational and/or Vocational
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Behave in accordance with ethical values regarding the collection, analysis and reporting of data.						5
2	Participate the design of work processes and systems with full quality.						5
3	Cooperate with other employees for the continuation of sustainability in the profession.					4

WORKLOAD & ECTS CREDITS OF THE COURSE UNIT
Workload for Learning & Teaching Activities
Type of the Learning Activites	Learning Activities (# of week)	Duration (hours, h)	Workload (h)
Lecture & In-Class Activities	14	3	42
Preliminary & Further Study	13	3	39
Land Surveying	0	0	0
Group Work	0	0	0
Laboratory	14	2	28
Reading	0	0	0
Assignment (Homework)	13	2	26
Project Work	0	0	0
Seminar	0	0	0
Internship	0	0	0
Technical Visit	0	0	0
Web Based Learning	0	0	0
Implementation/Application/Practice	0	0	0
Practice at a workplace	0	0	0
Occupational Activity	0	0	0
Social Activity	0	0	0
Thesis Work	0	0	0
Field Study	0	0	0
Report Writing	0	0	0
Final Exam	1	1	1
Preparation for the Final Exam	7	5	35
Mid-Term Exam	1	1	1
Preparation for the Mid-Term Exam	7	4	28
Short Exam	0	0	0
Preparation for the Short Exam	0	0	0
TOTAL	70	0	200