COURSE UNIT TITLE

: SOCIAL NETWORK ANALYSIS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
ECO 4124 SOCIAL NETWORK ANALYSIS ELECTIVE 3 0 0 6

Offered By

Economics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSISTANT PROFESSOR MEHMET ALDONAT BEYZATLAR

Offered to

Economics

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 Presentations
12 Presentations

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 MT Midterm
2 TP TermProject
3 FN Final
4 FCG FINAL COURSE GRADE MT * 0.40 +TP * 0.20 + FN * 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MT * 0.40 + TP * 0.20 + RST * 0.40


*** 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)

Will be announced.

Office Hours

Will be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 3 36
Preparations before/after weekly lectures 12 2 24
Preparation for midterm exam 1 15 15
Preparing presentations 1 15 15
Reading 10 2 20
Project Preparation 1 30 30
Midterm 1 2 2
TOTAL WORKLOAD (hours) 142

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14
LO.13355
LO.22554
LO.35555
LO.44555545