Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Поздовжній аналіз документів× | Лонгітюдний контент-аналіз× | |
|---|---|---|
| Галузь | Якісні методи | Якісні методи |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 2003–2009 (formalized in qualitative research methodology) | Mid-20th century onward; systematized alongside content analysis (Berelson, 1952; Krippendorff, 1980) |
| Автор методу≠ | Glenn A. Bowen (document analysis framework); Johnny Saldaña (longitudinal qualitative methods) | Developed within the content analysis tradition; longitudinal extensions widely applied since the mid-20th century in communication and political science research |
| Тип≠ | Qualitative longitudinal research design | Qualitative and mixed-methods research design |
| Основоположне джерело≠ | Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27–40. DOI ↗ | Krippendorff, K. (2018). Content Analysis: An Introduction to Its Methodology (4th ed.). Sage. ISBN: 978-1506395661 |
| Інші назви | longitudinal documentary research, longitudinal archival analysis, repeated document analysis, LDA | LCA, repeated content analysis, diachronic content analysis, trend content analysis |
| Пов'язані≠ | 3 | 5 |
| Підсумок≠ | Longitudinal document analysis is a qualitative research approach that systematically collects and analyzes documents at multiple time points to trace how phenomena, discourses, policies, or organizational practices change over time. By treating documents as primary data sources rather than supplementary evidence, researchers can reconstruct temporal trajectories, identify turning points, and understand how meaning evolves across extended periods without requiring direct participant contact. | Longitudinal Content Analysis (LCA) applies systematic content analysis to documents, media, or texts sampled at two or more time points in order to detect how themes, frames, language, or discourse patterns change or persist over time. Drawing on the established logic of content analysis, it adds a temporal dimension that allows researchers to chart trends, trace the evolution of representations, and test hypotheses about historical or social change. It is widely used in communication research, political science, media studies, and the health sciences. |
| ScholarGateНабір даних ↗ |
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