YMD416 Data Mining in New MediaIstanbul Okan UniversityDegree Programs Civil Engineering (English)General Information For StudentsDiploma SupplementErasmus Policy StatementNational Qualifications
Civil Engineering (English)
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: TR
Course Requisites:
Does the Course Require Work Experience?: No
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) 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 select and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively.
5) Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions.
6) Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7) Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions.
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) Knowledge on behavior according ethical principles, professional and ethical responsibility and standards used in engineering practices.
10) Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about 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 select and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively.
5) Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions.
6) Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7) Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions.
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) Knowledge on behavior according ethical principles, professional and ethical responsibility and standards used in engineering practices.
10) Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about 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

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