Compara mètodes

	Anàlisi Quantitativa de Contingut Multivariant	Anàlisi Quantitativa Comparativa de Continguts
Camp	Disseny de recerca	Disseny de recerca
Família	Process / pipeline	Process / pipeline
Any d'origen	1969–2000s	1952 (Berelson); comparative extensions prominent from 1980s onward
Autor original	Rooted in Holsti (1969) and Neuendorf (2002); multivariate extensions developed in communication and political science research from the 1970s onward	Bernard Berelson (quantitative content analysis); Kimberly Neuendorf (codebook systematization); Hallin & Mancini (comparative media application)
Tipus	Quantitative research design	Quantitative observational research design
Font seminal	Neuendorf, K. A. (2002). The Content Analysis Guidebook. Sage Publications. ISBN: 978-0761919773	Berelson, B. (1952). Content Analysis in Communication Research. Free Press.
Àlies	multivariate QCA, multivariate content analysis, MQCA, multivariate text analysis	CQCA, cross-national content analysis, comparative media content analysis, systematic comparative content analysis
Relacionats	6	5
Resum	Multivariate quantitative content analysis (MQCA) is a systematic, replicable approach to measuring multiple attributes of communication content simultaneously and examining how those attributes relate to each other or to external variables. It extends standard content analysis by applying multivariate statistical techniques — such as factor analysis, cluster analysis, regression, or MANOVA — to coded content data, enabling researchers to uncover complex patterns across many variables at once.	Comparative quantitative content analysis is a systematic, replicable method for counting and categorizing features of communication content — such as news coverage, social media posts, or policy documents — across two or more groups, time periods, outlets, or countries. By applying a standardized codebook to each comparison context, it reveals patterns of similarity and difference in how topics, frames, actors, or sentiments are represented, and allows statistical testing of those differences.