Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Srovnávací kvantitativní obsahová analýza× | Dlouhodobá kvantitativní obsahová analýza× | |
|---|---|---|
| Obor | Design výzkumu | Design výzkumu |
| Rodina | Process / pipeline | Process / pipeline |
| Rok vzniku≠ | 1952 (Berelson); comparative extensions prominent from 1980s onward | 1950s onward; longitudinal application widely adopted in media research by the 1970s–1980s |
| Tvůrce≠ | Bernard Berelson (quantitative content analysis); Kimberly Neuendorf (codebook systematization); Hallin & Mancini (comparative media application) | Developed within communication and media studies; codified by Berelson (1952) and extended by Riffe, Lacy, Fico |
| Typ | Quantitative observational research design | Quantitative observational research design |
| Původní zdroj≠ | Berelson, B. (1952). Content Analysis in Communication Research. Free Press. link ↗ | Riffe, D., Lacy, S., Watson, B., & Fico, F. (2019). Analyzing Media Messages: Using Quantitative Content Analysis in Research (4th ed.). Routledge. ISBN: 9781138490536 |
| Další názvy | CQCA, cross-national content analysis, comparative media content analysis, systematic comparative content analysis | longitudinal content analysis, repeated-measure content analysis, time-series content analysis, longitudinal QCA |
| Příbuzné | 5 | 5 |
| Shrnutí≠ | 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. | Longitudinal quantitative content analysis systematically codes and counts features of texts, images, or media messages gathered at two or more points in time, enabling researchers to track how content changes, how themes rise or fall in prevalence, and how media or institutional messaging responds to external events. The design merges the structured measurement logic of quantitative content analysis with the temporal tracking power of longitudinal observation. |
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