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.
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出典
- 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
このページの引用方法
ScholarGate. (2026, June 22). Automated (Computational) Content Analysis of Text. ScholarGate. https://scholargate.app/ja/communication/automated-content-analysis
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