Bandingkan metode

	Analisis Wacana	Teori Beralasan	Analisis Sentimen
Bidang	Penelitian Kualitatif	Penelitian Kualitatif	Penambangan Teks
Keluarga	Process / pipeline	Process / pipeline	Process / pipeline
Tahun asal	1989 (Fairclough); 1987 (Potter & Wetherell)	1967	—
Pencetus	Norman Fairclough; Jonathan Potter and Margaret Wetherell	Barney Glaser and Anselm Strauss	—
Tipe	Method	Method	NLP text-classification task
Sumber perintis	Fairclough, N. (1989). Language and power. Longman.	Glaser, B. G., & Strauss, A. L. (1967). The discovery of grounded theory: Strategies for qualitative research. Aldine.	Pang, B. & Lee, L. (2008). Opinion Mining and Sentiment Analysis. Foundations and Trends in Information Retrieval, 2(1-2), 1-135.
Alias	DA, Critical Discourse Analysis, Discursive Analysis	GT, Grounded Theory Approach	opinion mining, polarity detection, duygu analizi
Terkait	2	3	3
Ringkasan	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.	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.	Sentiment analysis, also called opinion mining, is a natural-language-processing task that detects the emotional tone of text — typically classifying it as positive, negative, or neutral. It turns unstructured opinion text into structured, quantifiable polarity signals using one of three families of approaches: sentiment lexicons, trained machine-learning classifiers, or pretrained transformer models.