ZURn6310 Quantitative Content Analysis

Faculty of Social Studies
Spring 2024
Extent and Intensity
1/1/0. 4 credit(s). Type of Completion: z (credit).
Teacher(s)
Mgr. et Mgr. Michal Tkaczyk, Ph.D. (lecturer)
Mgr. Petra Pichaničová (assistant)
Guaranteed by
Mgr. et Mgr. Michal Tkaczyk, Ph.D.
Department of Media Studies and Journalism – Faculty of Social Studies
Contact Person: Mgr. Boris Rafailov, Ph.D.
Supplier department: Department of Media Studies and Journalism – Faculty of Social Studies
Timetable
Fri 8:00–9:40 Rádio 544
Prerequisites
ZURn4108 Analysis of Quantitative Data
The course is addressed to students of the master's degree program, who are expected to have basic knowledge in the field of quantitative research methodology.
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The aim of the course is to acquaint the students with quantitative content analysis and equip them with required skills so they can design and conduct their own empirical research based on this method.
Learning outcomes
Upon the completion of the course, students will: • be able to demonstrate understanding of the principles of content analysis and the possibilities of its application in media communication research; • be able to design a research project based on content analysis; • be able to conduct own empirical research based on this method by herself or in team of peers; • be able to write a research report summarizing the results of content analysis
Syllabus
  • 1st Week: Introduction to the course 2nd Week: Content analysis: Basic principles, definitions and applications 3rd Week: Conceptual preparation of analysis: Conceptualization of research problem and research design 4th Week: Selection of content and sample construction 5th Week: Content analysis in applied research 6th Week: Data analysis in content analysis 7th Week: Operationalization of variables and selection of indicators 8th Week: Codebook development 9th Week: Validity, reliability and inter-coder reliability 10th Week: Self-study 11th Week: Content analysis of social media 12th Week: Self-study 13th Week: Presenting findings of CA
Literature
    required literature
  • RIFFE, Daniel, Stephen LACY and Frederick FICO. Analyzing media messages : using qualitative content analysis in research. Third edition. New York: Routledge, Taylor & Francis Group, 2014, xiv, 206. ISBN 9780415517669. info
  • KRIPPENDORFF, Klaus. Content analysis : an introduction to its methodology. 3rd ed. London: SAGE, 2013, xiv, 441. ISBN 9781412983150. info
  • NEUENDORF, Kimberly A. The content analysis guidebook. Thousand Oaks: SAGE Publications, 2002, xviii, 301. ISBN 0761919783. info
    recommended literature
  • SHOEMAKER, Pamela J. and Stephen D. REESE. Mediating the message in the 21st century : a media sociology perspective. Third edition. New York: Routledge, Taylor & Francis Group, 2014, xix, 287. ISBN 9780415989145. info
Teaching methods
Teaching methods in class include lectures, student presentations, discussion, problem solving. Students tasks include systematic and critical reading of academic literature, problem solving (elaboration of ongoing tasks and professional text).
Assessment methods
Class assignments
During the semester, students submit four class assignments: 1) Research project, 2) Research sample, 3) Coding book and coding sheet 4) Calculation of inter-coder agreement. Class assignments represent the partial steps / components necessary for the elaboration of the Final assignments.
Mini presentations in class
Students present the results of their work on solving class assignments to their colleagues.
Final assignment
Research project of CA.
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Autumn 2020, Spring 2021, Spring 2022, Spring 2023.
  • Enrolment Statistics (recent)
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