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.
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Course Content: |
Data analysis, data categorization and data interpretation, social media monitoring, social listening, data mining, insight production, product development, risk-crisis management, reporting. |
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 |
.. |
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Program Outcomes |
Level of Contribution |
1) |
Ability to think creatively and innovatively in industrial design discipline. |
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2) |
Ability to master professional material and production technologies and follow up developments and to effectively apply acquired knowledge in the projects |
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3) |
Ability to reflect cultural values to professional approaches |
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4) |
Ability to reach to original design solutions through critical approach to complex design problems and also foresee potential user needs. |
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5) |
Having the knowledge and ability to effectively use two and three dimensional design tools and technologies in industrial design |
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6) |
Ability to participate in teamwork in companies and to effectively participate in industrial design project management |
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7) |
Ability to have professional and ethical sense of responsibility |
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8) |
To work independently, to take responsiblity and to develop designerly sensitivities towards global problems |
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