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| Võrdlev kvantitatiivne sisuanalüüs× | Võrdlev küsitlusuuring× | |
|---|---|---|
| Valdkond | Uurimisdisain | Uurimisdisain |
| Perekond | Process / pipeline | Process / pipeline |
| Tekkeaasta≠ | 1952 (Berelson); comparative extensions prominent from 1980s onward | Mid-20th century onward |
| Looja≠ | Bernard Berelson (quantitative content analysis); Kimberly Neuendorf (codebook systematization); Hallin & Mancini (comparative media application) | Rooted in survey methodology traditions (Gallup, Likert, Lazarsfeld mid-20th century); comparative extension codified in social science research methods literature |
| Tüüp≠ | Quantitative observational research design | Quantitative non-experimental research design |
| Algallikas≠ | Berelson, B. (1952). Content Analysis in Communication Research. Free Press. link ↗ | Fowler, F. J. (2014). Survey Research Methods (5th ed.). Sage Publications. ISBN: 978-1452259000 |
| Rööpnimetused | CQCA, cross-national content analysis, comparative media content analysis, systematic comparative content analysis | comparative survey design, cross-group survey, multi-group survey research, comparative questionnaire study |
| Seotud≠ | 5 | 4 |
| Kokkuvõte≠ | 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. | Comparative survey research is a quantitative non-experimental design that systematically collects structured survey data from two or more clearly defined groups, populations, or contexts in order to identify, describe, and analyze similarities and differences among them. It extends basic survey research by making comparison the explicit organizing logic: rather than characterizing a single population, the goal is to detect how attitudes, behaviors, or outcomes vary across groups defined by nationality, culture, profession, demographic category, or time period. |
| ScholarGateAndmestik ↗ |
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