Automated Content Analysis
Automated content analysis is the computational measurement of text features at a scale impossible by hand, using natural-language processing and machine learning to classify, scale, or discover the content of large corpora. Synthesized for the social sciences by Grimmer and Stewart's 2013 'Text as Data,' it spans supervised classification, unsupervised discovery, and scaling, all unified by the principle that automated methods augment but do not replace careful human judgment and validation.
Læs hele metoden
Log ind med en gratis konto for at læse dette afsnit.
Metodekort
Nabolaget af beslægtede metoder — vælg en knude for at udforske.
Kilder
- Grimmer, J., & Stewart, B. M. (2013). Text as data: The promise and pitfalls of automatic content analysis methods for political texts. Political Analysis, 21(3), 267–297. DOI: 10.1093/pan/mps028 ↗
- Krippendorff, K. (2004). Content Analysis: An Introduction to Its Methodology (2nd ed.). Thousand Oaks, CA: Sage. ISBN: 9780761915454
Sådan citerer du denne side
ScholarGate. (2026, June 22). Automated (Computational) Content Analysis of Text. ScholarGate. https://scholargate.app/da/communication/automated-content-analysis
Hvilken metode?
Stil denne metode ved siden af dens nærmeste slægtninge, og læs dem side om side — biblioteket lægger bøgerne på bordet; valget er dit.
- Dictionary-Based Text AnalysisCommunication↔ sammenlign
- Manifest Content AnalysisCommunication↔ sammenlign
- Sentiment Analysis in CommunicationCommunication↔ sammenlign
- Topic Modeling for Communication ResearchCommunication↔ sammenlign
Refereret af
Lignende metoder
Har du fundet en fejl på denne side? Indberet den eller foreslå en rettelse →