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Longitudinal Content Analysis×Analýza diskurzu×
OborKvalitativní metodyKvalitativní výzkum
RodinaProcess / pipelineProcess / pipeline
Rok vznikuMid-20th century onward; systematized alongside content analysis (Berelson, 1952; Krippendorff, 1980)1989 (Fairclough); 1987 (Potter & Wetherell)
TvůrceDeveloped within the content analysis tradition; longitudinal extensions widely applied since the mid-20th century in communication and political science researchNorman Fairclough; Jonathan Potter and Margaret Wetherell
TypQualitative and mixed-methods research designMethod
Původní zdrojKrippendorff, K. (2018). Content Analysis: An Introduction to Its Methodology (4th ed.). Sage. ISBN: 978-1506395661Fairclough, N. (1989). Language and power. Longman. link ↗
Další názvyLCA, repeated content analysis, diachronic content analysis, trend content analysisDA, Critical Discourse Analysis, Discursive Analysis
Příbuzné52
ShrnutíLongitudinal 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.Discourse analysis is a qualitative research methodology that examines how language, communication, and power shape meaning, identity, and social reality. Developed across linguistics, sociology, and psychology (particularly by Norman Fairclough and Jonathan Potter), discourse analysis goes beyond content to analyze language use as a social practice that constitutes and reflects power relations, ideologies, and social structures.
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ScholarGatePorovnat metody: Longitudinal Content Analysis · Discourse Analysis. Získáno 2026-06-15 z https://scholargate.app/cs/compare