Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Análise de Conteúdo Quantitativa Longitudinal× | Pesquisa Descritiva× | |
|---|---|---|
| Área | Delineamento de pesquisa | Delineamento de pesquisa |
| Família | Process / pipeline | Process / pipeline |
| Ano de origem≠ | 1950s onward; longitudinal application widely adopted in media research by the 1970s–1980s | Late 19th century; formalized in social/behavioral sciences ~1960s–1980s |
| Autor original≠ | Developed within communication and media studies; codified by Berelson (1952) and extended by Riffe, Lacy, Fico | Francis Galton, Karl Pearson (early empirical tradition); formalized in social science by Fred Kerlinger |
| Tipo≠ | Quantitative observational research design | Non-experimental quantitative research design |
| Fonte seminal≠ | Riffe, D., Lacy, S., Watson, B., & Fico, F. (2019). Analyzing Media Messages: Using Quantitative Content Analysis in Research (4th ed.). Routledge. ISBN: 9781138490536 | Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (4th ed.). Sage. ISBN: 978-1452226101 |
| Outros nomes | longitudinal content analysis, repeated-measure content analysis, time-series content analysis, longitudinal QCA | descriptive study, descriptive survey design, observational descriptive research, non-experimental descriptive research |
| Relacionados≠ | 5 | 3 |
| Resumo≠ | 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. | Descriptive research is a non-experimental quantitative design that systematically documents the characteristics, frequencies, or distributions of variables in a defined population at a given point in time. It answers 'what is' questions — who, what, when, where, and how much — without manipulating variables or drawing causal conclusions. It is one of the most widely used research designs across the social, behavioral, health, and education sciences. |
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