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About the Programme Academic Staff Program Qualifications Lessons Matrix of Course & Program Qualifications Turkish Qualifications Framework (TQF) TQF & Program Qualifications
  1. Graduate School
  2. Department of Turkish Language and Literature
  3. Master of Science (MSc) in Contemporary Turkish Language
  4. Course Structure Diagram with Credits
  5. Text- and Document-Based Analysis Methods
  6. Description
  • Description
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Last Updated: 21/05/2026

Code - Course Title Course Type Laboratory + Practice ECTS
TDE704 - Text- and Document-Based Analysis Methods II. SEMESTER 3 +0 6.0
Language of Instruction Türkçe
Course Type Elective Courses
Course Instructor(s) PROF. DR. EMİNE KOLAÇ
Mode of Delivery The mode of delivery of this course is face-to-face
Place of Delivery
Used Educational Platforms
Prerequisites None
Courses Recomended None
Recommended Resources Andres, A. (2009). Measuring academic research: How to undertake a bibliometric study. Chandos Publishing. https://doi.org/10.1533/9781780630182Geiger, N., & Kufenko, V. (2019). Business cycles and economic crises: A bibliometric and economic history. Routledge.Briner, R. B. ve Denyer, D. (2012). Systematic review and evidence synthesis as a practice and scholarship tool. The Oxford Handbook of Evidence-Based Management içinde (ss. 112–129). Oxford University Press. doi:10.1093/oxfordhb/9780199763986.013.0007Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007Chatterjee, P., Saha, A., Kadry, S., & Demir, G. (Eds.). (2025). Bibliometric analyses in data-driven decision-making. John Wiley & Sons. https://doi.org/10.1002/9781394302581Murat, D. A. L., & İlhami, A. Y. (Eds.). (2025). Bibliyometrik Analiz III. Akademisyen Kitabevi.
Work Placement None
Aims of the Course

Weeks Learning Outcomes Topics Teaching Methods
Week - 1 Text and Document-Based Analysis: Basic concepts, scope and place in the research process
Week - 2 Descriptive Analysis: Description, data organization and initial interpretation process
Week - 3 Document Analysis: Text examination, document types and source quality
Week - 4 Source Selection: Determining the texts and documents to be examined
Week - 5 Data Collection Process: Access to documents, identification of limitations and record organization
Week - 6 Content Analysis: Coding, category formation and theme development
Week - 7 Coding Process: Coding unit, code list and coder consistency
Week - 8 Category and Theme Development: Establishing relationships among data
Week - 9 Analysis Process: Data classification, pattern identification and interpretation
Week - 10 AI-Supported Analysis Tools: Data organization, integration and preliminary examination
Week - 11 Use of AI-Supported Analysis Tools: Coding, comparison and report preparation
Week - 12 Validity and Reliability: Internal validity, external validity, internal reliability and external reliability
Week - 13 Inter-Coder Agreement and Data Diversity: Consistency, comparison and verification process
Week - 14 Reporting: Presentation of findings, use of quotations, academic writing and editing

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Assessment Method and Passing Requirements
Quamtity Percentage (%)
Toplam (%)

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