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Prekrižna kvantitativna analiza sadržaja×Kvantitativna analiza sadržaja×
PodručjeDizajn istraživanjaDizajn istraživanja
ObiteljProcess / pipelineProcess / pipeline
Godina nastankaMid-20th century (formalized 1952–2000s)1950s (Berelson 1952; Krippendorff 1980/2004)
TvoracBerelson, B.; Krippendorff, K.; Neuendorf, K. A.Bernard Berelson; later systematised by Klaus Krippendorff
VrstaQuantitative observational research designQuantitative observational research method
Temeljni izvorNeuendorf, K. A. (2002). The Content Analysis Guidebook. Sage Publications. ISBN: 978-0761919773Krippendorff, K. (2004). Content Analysis: An Introduction to Its Methodology (2nd ed.). Sage. ISBN: 978-0761915454
Drugi naziviCS-QCA, cross-sectional content analysis, single-timepoint content analysis, quantitative media content analysisQCA, manifest content analysis, systematic content analysis, frequency-based content analysis
Srodne44
SažetakCross-sectional quantitative content analysis is an observational research design in which a systematically drawn sample of communicative content — news articles, social media posts, advertisements, or other symbolic material — is collected at a single point in time and coded using pre-defined numerical categories to describe or test hypotheses about patterns, frequencies, or associations within that content.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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ScholarGateUsporedite metode: Cross-sectional Quantitative Content Analysis · Quantitative Content Analysis. Preuzeto 2026-06-17 s https://scholargate.app/hr/compare