Sociology
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:

Common Pool

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) Gains the ability to interpret social developments with the theoretical knowledge that is acquired and a critical perspective.
2) Has knowledge about other disciplines and is open to lifelong learning to be able to success interdisciplinary work.
3) Has the ability to observe social, scientific and ethical values in the stages of data collection, interpretation and announcement while conducting research in the field.
4) Graduates with a good knowledge of at least one foreign language and one foreign language at the entry level.
5) Gains a professional perspective with good observation ability and empathy.
6) Gains the ability to collect local, national and international data and conduct research in the field of social science.
7) Can make explanations to expert or non-expert audiences about their field or social issues, inform them and convey their thoughts, problems and solutions clearly in written and oral form.
8) Adopts various internship programs and applied studies.
9) Gains knowledge to work as a researcher, consultant or expert in the public or private sector.
10) Complies with the ethical rules accepted and encouraged by TÜBİTAK, YÖK and TÜBA and universal science within the context of research, and education.

Course - Learning Outcome Relationship

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

	Program Outcomes	Level of Contribution
1)	Gains the ability to interpret social developments with the theoretical knowledge that is acquired and a critical perspective.
2)	Has knowledge about other disciplines and is open to lifelong learning to be able to success interdisciplinary work.	5
3)	Has the ability to observe social, scientific and ethical values in the stages of data collection, interpretation and announcement while conducting research in the field.
4)	Graduates with a good knowledge of at least one foreign language and one foreign language at the entry level.
5)	Gains a professional perspective with good observation ability and empathy.
6)	Gains the ability to collect local, national and international data and conduct research in the field of social science.
7)	Can make explanations to expert or non-expert audiences about their field or social issues, inform them and convey their thoughts, problems and solutions clearly in written and oral form.
8)	Adopts various internship programs and applied studies.
9)	Gains knowledge to work as a researcher, consultant or expert in the public or private sector.
10)	Complies with the ethical rules accepted and encouraged by TÜBİTAK, YÖK and TÜBA and universal science within the context of research, and education.

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