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

General course introduction information

Course Code:

YMD416

Course Name:

Data Mining in New Media

Course Semester:

Spring

Course Credits:

Theoretical	Practical	Credit	ECTS
3	0	3	7

Language of instruction:

Course Requisites:

Does the Course Require Work Experience?:

Type of course:

University Elective

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):

Course Assistants:

Course Objective and Content

Course Objectives:

Data mining, which has an important place in determining the target audience-communication language and strategy in the field of communication and marketing, also tells what the content density is saying positively and negatively and what it usually talks about. In addition, it is also effective in producing insight, product development and risk-crisis management.
The aim of the course is to enable students, who aim to take part in the new media sector, to manage social media effectively and to communicate correctly with consumers on social media by analyzing content.

Course Content:

Data analysis, data categorization and data interpretation, social media monitoring, social listening, data mining, insight production, product development, risk-crisis management, reporting.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) To be able to comprehend the basic concepts required for data tracking and analysis in new media, to explain the basic, theoretical and applied information for data, data analysis, data tracking, monitoring, insight and reporting.
2 - Skills
Cognitive - Practical
3 - Competences
Communication and Social Competence
1) To carry out studies for social area by using data mining techniques with a sense of social responsibility. To be able to develop solutions to social problems with insights gained through the work carried out.
Learning Competence
1) To be able to transfer basic knowledge and gains about data mining to other disciplines of communication. To be able to evaluate the literature of new media and communication discipline in the perspective of data mining. To be able to use the applications and tools developed for data mining competently.
Field Specific Competence
1) To be able to use the monitoring and data processing programs developed specifically for new communication technologies and social networks, to report the results obtained and to transform them into results and findings that the society can make sense of.
Competence to Work Independently and Take Responsibility
1) Being able to take data with the right keywords and analyze and apply it independently for new purposes and needs in new media platforms. Ability to plan and manage activities for the development of employees under their responsibility for analyzing data and producing insights.

Lesson Plan

Week	Subject	Related Preparation
1)	Information transfer for the digital communication industry. What is data mining and where is it used?	None
2)	Focus group review with in-class practice. PDPL rules in data mining.	none
3)	Group examination on social media and evaluation of results with in-class practice. Examples of data mining research in new media.	none
4)	Personal and corporate profile review with In-class practice.	none
5)	Brand language and brand strategy. Analysis and determination of language and strategy with data mining.	none
6)	Student reviews and presentations on brand language and brand strategy.	none
7)	Midterm Exam.	..
8)	Risk and crisis management in social media. Important examples of crisis in the history of social media and the role of data mining in crisis communication.	none
10)	The importance of data mining for accurate and effective insight. Insight examples reached by data mining.	none
11)	Agenda review and insight capture with data mining. Presentation of captured insights.	none
12)	What is Responding management, how is it done? What are the rules? Why is it important for accounts in the new media?	none
13)	Coding system in Data Mining. Sample coding with the installed system.	none
14)	How to use the data coding tool Somera? What are the features? Research examples with data mining in new media.	https://www.somera.com.tr/
15)	Final Exam	..

Sources

Course Notes / Textbooks:	Baloğlu, A. (2015), Sosyal Medya Madenciliği, Beta Yayınları.
References:	Baloğlu, A. (2015), Sosyal Medya Madenciliği, Beta Yayınları.

Course-Program Learning Outcome Relationship

Learning Outcomes	1	3	4	5	6
Program Outcomes
1) Describe the basic structure, development and normal mechanisms of the human in terms of molecules, cells, tissues, organs and systems
2) Investigates the abnormal structures and mechanisms in the human body, explains with the information depending on high quality scientific research, evaluates the reason of the diseases regarding in the interaction of the individual with his environment
3) Gain knowledge about basic and clinical medicine
4) Apply the knowledge, skills and attitudes required by the patient management in accordance with the modern medical concept.
5) Apply basic medical procedures necessary for diagnosis and treatment of diseases
6) Perform first level treatment for common diseases in the community based on scientific data and by using highly effective methods
7) Treat patients in emergency situations and transport the patient when needed
8) Perform preventive medicine and forensic medicine applications
9) Evaluate the effects of environmental factors on human health
10) Gain knowledge about the structure and functioning of the National Health System
11) Advocate for the health promotion, and development of health care services for the benefits of the individuals in the community
12) Define legal responsibilities and ethical principles
13) Act in accordance with professional values, ethical principles and legal regulations
14) Take responsibility for lifelong learning and personal assessment
15) Organize and attend to scientific meetings and conduct scientific projects
16) Know at least one common foreign language sufficient to keep up with current medical literature and communicate with peers; and use statistics and computer programmes to evaluate scientific studies

Course - Learning Outcome Relationship

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

	Program Outcomes	Level of Contribution
1)	Describe the basic structure, development and normal mechanisms of the human in terms of molecules, cells, tissues, organs and systems
2)	Investigates the abnormal structures and mechanisms in the human body, explains with the information depending on high quality scientific research, evaluates the reason of the diseases regarding in the interaction of the individual with his environment
3)	Gain knowledge about basic and clinical medicine
4)	Apply the knowledge, skills and attitudes required by the patient management in accordance with the modern medical concept.
5)	Apply basic medical procedures necessary for diagnosis and treatment of diseases
6)	Perform first level treatment for common diseases in the community based on scientific data and by using highly effective methods
7)	Treat patients in emergency situations and transport the patient when needed
8)	Perform preventive medicine and forensic medicine applications
9)	Evaluate the effects of environmental factors on human health
10)	Gain knowledge about the structure and functioning of the National Health System
11)	Advocate for the health promotion, and development of health care services for the benefits of the individuals in the community
12)	Define legal responsibilities and ethical principles
13)	Act in accordance with professional values, ethical principles and legal regulations
14)	Take responsibility for lifelong learning and personal assessment
15)	Organize and attend to scientific meetings and conduct scientific projects
16)	Know at least one common foreign language sufficient to keep up with current medical literature and communicate with peers; and use statistics and computer programmes to evaluate scientific studies

Learning Activity and Teaching Methods

Field Study
Expression
Individual study and homework
Lesson
Group study and homework
Reading
Homework
Project preparation
Case Study
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
Presentation
Peer Review
Bilgisayar Destekli Sunum
Case study presentation

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Application	1	% 20
Homework Assignments	2	% 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	16	48
Application	14	28
Study Hours Out of Class	16	80
Homework Assignments	16	32
Midterms	1	3
Final	2	6
Total Workload		197