COURSE UNIT TITLE

: TOPICS IN SOCIAL NETWORK ANALYSIS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
ECN 5057 TOPICS IN SOCIAL NETWORK ANALYSIS ELECTIVE 3 0 0 6

Offered By

Economics (English)

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR MEHMET ALDONAT BEYZATLAR

Offered to

Economics (English)

Course Objective

Everything is connected: people, information, events and places. A practical way of making sense of the tangle of connections is to analyze them as networks. Social Network Analysis (SNA) is a set of analytical methods and theories that study the pattern of relations among actors. Social networks are everywhere and play a role in substantive problems that cut across many subjects and disciplines. Any research problem that involves actors who have relations with each other, and relations that can be observed and measured, may benefit from Social Network Analysis. This course aims to provide students about the structure and evolution of networks, drawing on knowledge from economics.

Learning Outcomes of the Course Unit

1   Demonstrate understanding of basic concepts of network analysis so that students can recognize what are networks and what use is it to study them.
2   Identify different types of networks in order to analyze their impacts under different structures.
3   Be able to use software so that students can analyze different network structures.
4   Make presentations and prepare a term project on a given subject with the purpose of doing descriptive analysis of different networks.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Foundations of SNA
2 Networks
3 Ego-Networks
4 Global Networks
5 Applications of SNA
6 SNA and Online Social Networks
7 Economics and SNA
8 Network Data Collection
9 Network Metrics
10 Network Metrics and Graphs
11 Network Metrics and Graphs
12 Network Metrics and Graphs

Recomended or Required Reading

1. Stanley Wasserman and Katherine Faust. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press.
2. Robert Hanneman. (2005). Introduction to Social Networks. (A free online text-book).

Planned Learning Activities and Teaching Methods

1. Lectures
2. Readings
3. Data Search and Empirical Analysis

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 FCG FINAL COURSE GRADE
3 FCGR FINAL COURSE GRADE MTE * 0.40 + FCG* 0.60
4 RST RESIT
5 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 + RST* 0.60


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

1. The learner will clearly define social network analysis' concepts.
2. The learner will use necessary data and empirical tools to explain the interaction through networks.
3. The learner will recognize economic issues defined in reserved books and resources at the library.

Language of Instruction

English

Course Policies and Rules

1. Attending at least 70 percent of lectures is mandatory.
2. Plagiarism of any type will result in disciplinary action.

Contact Details for the Lecturer(s)

mehmet.beyzatlar@deu.edu.tr

Office Hours

Please make an appointment by e-mail.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 3 36
Preparations before/after weekly lectures 12 3 36
Preparation for midterm exam 1 15 15
Preparation for final exam 1 15 15
Reading 10 2 20
Preparing presentations 2 10 20
Midterm 1 3 3
Final 1 3 3
TOTAL WORKLOAD (hours) 148

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.154
LO.253
LO.3454
LO.455