Salīdzināt metodes

	Hierarhiskā kvantitatīvā satura analīze	Kvantitatīvā satura analīze	Tematiskā analīze
Nozare	Pētījuma dizains	Pētījuma dizains	Kvalitatīvie pētījumi
Saime	Process / pipeline	Process / pipeline	Process / pipeline
Izcelsmes gads	1980s–1990s (formalized in Krippendorff 1980; elaborated through subsequent editions)	1950s (Berelson 1952; Krippendorff 1980/2004)	2006
Autors	Klaus Krippendorff (hierarchical category systems formalized in content analysis methodology)	Bernard Berelson; later systematised by Klaus Krippendorff	Virginia Braun and Victoria Clarke
Tips	Quantitative research design	Quantitative observational research method	Method
Pirmavots	Krippendorff, K. (2018). Content Analysis: An Introduction to Its Methodology (4th ed.). Sage. ISBN: 978-1506395678	Krippendorff, K. (2004). Content Analysis: An Introduction to Its Methodology (2nd ed.). Sage. ISBN: 978-0761915454	Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.
Citi nosaukumi	hierarchical coding content analysis, nested category content analysis, tree-structured content analysis, HQCA	QCA, manifest content analysis, systematic content analysis, frequency-based content analysis	TA, Reflexive Thematic Analysis
Saistītās	2	4	3
Kopsavilkums	Hierarchical quantitative content analysis is a systematic method for coding and counting text or media content using nested, tree-structured category schemes. Rather than a flat list of mutually exclusive codes, categories are organized into parent-child levels — broad themes subdivide into specific sub-themes — enabling researchers to aggregate or disaggregate frequencies at any level of the hierarchy and to produce richly structured numerical summaries of large corpora.	Quantitative content analysis is a systematic, replicable method for converting the manifest content of text, images, or other recorded communication into numerical data. By applying a pre-specified codebook to a defined corpus and counting or scaling the resulting categories, researchers obtain frequency distributions, proportions, and relationships that can be subjected to standard statistical tests. It is the dominant method for large-scale, objective analysis of media, documents, social media posts, policy texts, and similar materials.	Thematic Analysis (TA) is a qualitative research methodology for identifying, analyzing, and reporting patterns (themes) in qualitative data. Developed systematically by Virginia Braun and Victoria Clarke (2006), TA is flexible and accessible, applicable across diverse theoretical frameworks and data types, making it one of the most widely used qualitative methods in psychology, health research, and social sciences.