Sammenlign metoder

	Innholdsanalyse	Grounded Theory	Undersøkelsesforskning
Fagfelt	Kvalitativ	Kvalitativ forskning	Forskningsdesign
Familie	Process / pipeline	Process / pipeline	Process / pipeline
Opprinnelsesår	Systematised through Krippendorff's methodology work; 4th edition 2018	1967	Late 19th century; methodologically systematised 1940s–1960s
Opphavsperson	Klaus Krippendorff (systematic formulation); roots in early 20th-century communications research	Barney Glaser and Anselm Strauss	Francis Galton, Charles Booth, and early social statisticians; systematised by Paul Lazarsfeld and colleagues at Columbia in the 1940s
Type	Qualitative / mixed-method research technique	Method	Quantitative (and mixed) non-experimental design
Opprinnelig kilde	Krippendorff, K. (2018). Content Analysis: An Introduction to Its Methodology (4th ed.). Sage. ISBN: 978-1506395661	Glaser, B. G., & Strauss, A. L. (1967). The discovery of grounded theory: Strategies for qualitative research. Aldine.	Fowler, F. J. (2014). Survey Research Methods (5th ed.). Sage Publications. ISBN: 978-1452259000
Alias	İçerik Analizi, systematic content coding, quantitative content analysis	GT, Grounded Theory Approach	survey methodology, questionnaire research, survey design, survey study
Relaterte	5	3	4
Sammendrag	Content analysis is a systematic research technique for reducing text, visual, or media material into coded categories so that patterns can be counted, compared, and interpreted. Formalised by Klaus Krippendorff in his widely cited methodology textbook (latest edition 2018), the method sits at the boundary of qualitative and quantitative inquiry: it imposes structured, replicable coding on inherently meaning-laden material.	Grounded Theory (GT) is a systematic qualitative research methodology in which theory emerges directly from data through iterative analysis, rather than being imposed before data collection. Developed by Barney Glaser and Anselm Strauss in 1967, GT prioritizes generating explanatory frameworks grounded in evidence.	Survey research is a quantitative (and sometimes mixed-methods) design in which a researcher collects standardised self-report data from a sample drawn from a defined population, using a questionnaire or structured interview. It is the dominant non-experimental strategy for describing population characteristics, estimating prevalence, mapping attitude distributions, and testing bivariate or multivariate associations across social, behavioural, and health sciences.