Industrial Engineering
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

General course introduction information

Course Code:

YMD303

Course Name:

Web and Social Network Analysis

Course Semester:

Fall

Course Credits:

Theoretical	Practical	Credit	ECTS
3	0	3	5

Language of instruction:

Course Requisites:

Does the Course Require Work Experience?:

Type of course:

Compulsory

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Öğr.Gör. HAMZA ŞAMLIOĞLU

Course Lecturer(s):

Öğr.Gör. ALTUĞ SAMİ İÇİLENSU

Course Assistants:

Course Objective and Content

Course Objectives:	The aim of the course is to examine the relationships between user and data based network activities on web sites and social media platforms, analyze these relationships, reveal different connections and patterns, capture and evaluate insights and take new actions in communication plans.
Course Content:	Virtual Network and Virtual Community Concepts, Network Science and Social Networks, Network Types, Social Network Analysis, Web Analysis, Random Network Models, nodes, relationships, neighborhood matrix, node degree, NodeXL.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) To be able to explain network science, web technologies, the development of network analysis and terms, theories and models related to network analysis, to follow and dominate all kinds of developments in Social Network analysis.
2 - Skills
Cognitive - Practical
1) To gain the ability to find and extract information from data stacks on online platforms and information networks, to use theoretical and factual information acquired for Web analysis and social network analysis in personal production, to analyze existing studies, to be able to approach critically.
3 - Competences
Communication and Social Competence
1) To analyze social networks and digital platforms with the awareness of social responsibility, to use the data obtained for constructive projects and applications for the social environment in which it lives.
Learning Competence
1) Learning programs developed for network analysis, using them in accordance with the target. Critical approach to both the data obtained from the analysis and the methods of analysis, making and suggesting changes, reaching the target by determining the learning needs and planning.
Field Specific Competence
1) Act and make decisions in accordance with ethical and scientific values for both communication discipline and web-social network analysis.
Competence to Work Independently and Take Responsibility
1) To be able to conduct an advanced study on network analysis independently and to produce for the portfolio. To take responsibility as an individual and a team member in order to analyze networks and social media and extract meaningful data.

Lesson Plan

Week	Subject	Related Preparation
1)	What is Social Network and Web page?
2)	Social Media Communities. Virtual community structures.
3)	Basic concepts of social network and web analysis.
4)	Random Network Models.
5)	Network centrality and Network prestige.
6)	Social Network Analysis Applications.
7)	Midterm Exam.
8)	Data Pre-Processing Processes.
9)	Data mining methods.
10)	Text Mining and Sentiment Analysis.
11)	Data reading and Insight.
12)	Network analysis studies with NodeXL application.
13)	Network analysis studies with NodeXL application -2.
14)	Overview of the course.

Sources

Course Notes / Textbooks:	Tunalı, V. (2016). Sosyal Ağ Analizine Giriş. İstanbul: Nobel Yayınları.
References:	Derek Hansen, Ben Shneiderman, Marc A. Smith. (2010). Analyzing Social Media Networks with NodeXL: Insights from a Connected World, Morgan Kaufmann, 2010

Course-Program Learning Outcome Relationship

Learning Outcomes	1	2	3	4	5	6
Program Outcomes
1) Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied information in these areas to model and solve engineering problems.
2) Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modelling methods for this purpose.
3) Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way so as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues according to the nature of the design.)
4) Ability to devise, select, and use modern techniques and tools needed for engineering practice; ability to employ information technologies effectively.
5) Ability to design and conduct experiments, gather data, analyse and interpret results for investigating engineering problems.
6) Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7) Ability to communicate effectively i Turkish, both orally and in writing; knowledge of a minimum of one foreign language.
8) Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
9) Awareness of professional and ethical responsibility.
10) Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.
11) Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of engineering solutions.

Course - Learning Outcome Relationship

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied information in these areas to model and solve engineering problems.
2)	Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modelling methods for this purpose.
3)	Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way so as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues according to the nature of the design.)
4)	Ability to devise, select, and use modern techniques and tools needed for engineering practice; ability to employ information technologies effectively.
5)	Ability to design and conduct experiments, gather data, analyse and interpret results for investigating engineering problems.
6)	Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7)	Ability to communicate effectively i Turkish, both orally and in writing; knowledge of a minimum of one foreign language.
8)	Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
9)	Awareness of professional and ethical responsibility.
10)	Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.
11)	Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of engineering solutions.

Learning Activity and Teaching Methods

Expression
Individual study and homework
Lesson
Group study and homework
Lab
Reading
Homework
Problem Solving
Report Writing
Web Based Learning

Assessment & Grading Methods and Criteria

Written Exam (Open-ended questions, multiple choice, true-false, matching, fill in the blanks, sequencing)
Homework
Application
Individual Project
Group project
Reporting
Bilgisayar Destekli Sunum

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Application	2	% 20
Midterms	1	% 30
Final	1	% 50
total		% 100
PERCENTAGE OF SEMESTER WORK		% 50
PERCENTAGE OF FINAL WORK		% 50
total		% 100

Workload and ECTS Credit Grading

Activities	Number of Activities	Workload
Course Hours	14	42
Study Hours Out of Class	15	45
Homework Assignments	16	48
Midterms	1	3
Final	1	3
Total Workload		141