COURSE UNIT TITLE

: FOUNDATIONS AND APPLICATIONS OF SOCIAL NETWORK ANALYSIS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
CSE 5088 FOUNDATIONS AND APPLICATIONS OF SOCIAL NETWORK ANALYSIS ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR ZERRIN IŞIK

Offered to

Computer Engineering (Non-Thesis-Evening) (English)
Computer Engineering Non-Thesis (English)
Computer Engineering (English)
Computer Engineering (English)
COMPUTER ENGINEERING (ENGLISH)

Course Objective

This course aims to introduce the fundamentals of social network analysis, presents practical tools to be used in this process and discusses different case studies.

Learning Outcomes of the Course Unit

1   Define fundamental theory about graph theory related with SNA
2   Describe and build basic social networking Platforms
3   Use practical tools to collect, analyze, reduction and visualize network data
4   Design and implement an SNA project for a given domain

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 History of social network analysis 
2 Basics of graph theory, linear algebra and statistics
3 Data collection, cleaning
4 Introduction to network data formats (R coding)
5 Social network types (random, small World)
6 Topology prediction
7 Centrality metrics, PageRank
8 Group and module analysis
9 Centrality and module analysis with examples (R coding)
10 Information spread, epidemics
11 Network visualization with examples (R coding)
12 Practical tutorials with some hands-on practice using a SNA tool
13 Case Study: Bioinformatics
14 Project presentations

Recomended or Required Reading

1. Alhajj Reda, Rokne Jon (Eds.), Encyclopedia of Social Network Analysis and Mining, Springer, In 3 volume, 2014, ISBN 978-1-4614-6169-2.

2. John Scott, Social Network Analysis, SAGE Publications, 2017.

3. Recent scientific publications

Planned Learning Activities and Teaching Methods

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG ASSIGNMENT
2 PRS PRESENTATION
3 FCG FINAL COURSE GRADE ASG * 0.50 + PRS * 0.50


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

Further Notes About Assessment Methods

None

Assessment Criteria

Homeworks, quizzes and final project

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Assoc.Prof.Dr.Zerrin IŞIK
Dokuz Eylul University, Dept of Computer Engineering
Tinaztepe, 35160 Izmir, Turkey
Tel: 232-3017413
E-mail: zerrin@cs.deu.edu.tr

Office Hours

TBA

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 15 3 45
0
Preparations before/after weekly lectures 15 4 60
Preparing assignments 4 10 40
Preparing presentations 1 20 20
Reading 2 15 30
TOTAL WORKLOAD (hours) 195

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11
LO.153
LO.2553
LO.35553
LO.455535555

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

Copyright 2015 DEÜ. BİD

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