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| Analisi Quantitativa Longitudinale del Contenuto× | Ricerca di Tendenza× | |
|---|---|---|
| Campo | Disegno della ricerca | Disegno della ricerca |
| Famiglia | Process / pipeline | Process / pipeline |
| Anno di origine≠ | 1950s onward; longitudinal application widely adopted in media research by the 1970s–1980s | Mid-20th century (formalised in social science methodology ~1950s–1960s) |
| Ideatore≠ | Developed within communication and media studies; codified by Berelson (1952) and extended by Riffe, Lacy, Fico | Earl Babbie and survey research tradition |
| Tipo≠ | Quantitative observational research design | Quantitative longitudinal research design |
| Fonte seminale≠ | 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 |
| Alias | longitudinal content analysis, repeated-measure content analysis, time-series content analysis, longitudinal QCA | trend study, trend survey, longitudinal trend study, time-series survey |
| Correlati≠ | 5 | 4 |
| Sintesi≠ | 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. | Trend research is a longitudinal quantitative design that tracks changes in a characteristic of a general population over time by surveying different, independently drawn samples at two or more time points. Unlike panel studies, the same individuals are not followed; rather, each wave draws a fresh sample from the same population, allowing researchers to detect population-level shifts in attitudes, behaviours, or conditions while avoiding the attrition and panel conditioning problems of repeated-measures designs. |
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