Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Análise de Conteúdo Quantitativa× | Análise de Conteúdo Quantitativa Longitudinal× | |
|---|---|---|
| Área | Delineamento de pesquisa | Delineamento de pesquisa |
| Família | Process / pipeline | Process / pipeline |
| Ano de origem≠ | 1950s (Berelson 1952; Krippendorff 1980/2004) | 1950s onward; longitudinal application widely adopted in media research by the 1970s–1980s |
| Autor original≠ | Bernard Berelson; later systematised by Klaus Krippendorff | Developed within communication and media studies; codified by Berelson (1952) and extended by Riffe, Lacy, Fico |
| Tipo≠ | Quantitative observational research method | Quantitative observational research design |
| Fonte seminal≠ | Krippendorff, K. (2004). Content Analysis: An Introduction to Its Methodology (2nd ed.). Sage. ISBN: 978-0761915454 | Riffe, D., Lacy, S., Watson, B., & Fico, F. (2019). Analyzing Media Messages: Using Quantitative Content Analysis in Research (4th ed.). Routledge. ISBN: 9781138490536 |
| Outros nomes | QCA, manifest content analysis, systematic content analysis, frequency-based content analysis | longitudinal content analysis, repeated-measure content analysis, time-series content analysis, longitudinal QCA |
| Relacionados≠ | 4 | 5 |
| Resumo≠ | 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. | 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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