Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Количественный кросс-секционный контент-анализ× | Лонгитюдный количественный контент-анализ× | |
|---|---|---|
| Область | Дизайн исследования | Дизайн исследования |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | Mid-20th century (formalized 1952–2000s) | 1950s onward; longitudinal application widely adopted in media research by the 1970s–1980s |
| Автор метода≠ | Berelson, B.; Krippendorff, K.; Neuendorf, K. A. | Developed within communication and media studies; codified by Berelson (1952) and extended by Riffe, Lacy, Fico |
| Тип | Quantitative observational research design | Quantitative observational research design |
| Основополагающий источник≠ | Neuendorf, K. A. (2002). The Content Analysis Guidebook. Sage Publications. ISBN: 978-0761919773 | Riffe, D., Lacy, S., Watson, B., & Fico, F. (2019). Analyzing Media Messages: Using Quantitative Content Analysis in Research (4th ed.). Routledge. ISBN: 9781138490536 |
| Другие названия | CS-QCA, cross-sectional content analysis, single-timepoint content analysis, quantitative media content analysis | longitudinal content analysis, repeated-measure content analysis, time-series content analysis, longitudinal QCA |
| Связанные≠ | 4 | 5 |
| Сводка≠ | Cross-sectional quantitative content analysis is an observational research design in which a systematically drawn sample of communicative content — news articles, social media posts, advertisements, or other symbolic material — is collected at a single point in time and coded using pre-defined numerical categories to describe or test hypotheses about patterns, frequencies, or associations within that content. | 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. |
| ScholarGateНабор данных ↗ |
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