Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Hierarhiskā kvantitatīvā satura analīze× | Kvantitatīvā satura analīze× | |
|---|---|---|
| Nozare | Pētījuma dizains | Pētījuma dizains |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 1980s–1990s (formalized in Krippendorff 1980; elaborated through subsequent editions) | 1950s (Berelson 1952; Krippendorff 1980/2004) |
| Autors≠ | Klaus Krippendorff (hierarchical category systems formalized in content analysis methodology) | Bernard Berelson; later systematised by Klaus Krippendorff |
| Tips≠ | Quantitative research design | Quantitative observational research 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 |
| 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 |
| Saistītās≠ | 2 | 4 |
| 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. |
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