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) |
Sports management students have advanced level theoretical and practical knowledge supported by textbooks, application tools and other resources which contain up-to-date information in the field. |
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2) |
Sport management students can transfer their opinions and suggestions for solutions to problems in written and orally, and share their ideas and solutions with problems by supporting them with qualitative and quantitative data.
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3) |
Sports management students act in accordance with social, scientific, cultural and ethical values in the stages of collecting, interpreting, applying and announcing the data related to the field. |
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4) |
Sports management students can use the advanced theoretical and practical knowledge gained in the field and use the advanced knowledge and skills in the field to interpret and evaluate the data, to identify problems, to analyze problems, to develop solutions based on research and evidence. |
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5) |
Sports management students can conduct an advanced study independently and take responsibility as an individual and team member in order to solve unforeseen complex problems encountered in the applications related to their field.
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