Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Дискурс-анализ× | Анализ тональности× | |
|---|---|---|
| Область≠ | Качественные исследования | Интеллектуальный анализ текста |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1989 (Fairclough); 1987 (Potter & Wetherell) | — |
| Автор метода≠ | Norman Fairclough; Jonathan Potter and Margaret Wetherell | — |
| Тип≠ | Method | NLP text-classification task |
| Основополагающий источник≠ | Fairclough, N. (1989). Language and power. Longman. link ↗ | Pang, B. & Lee, L. (2008). Opinion Mining and Sentiment Analysis. Foundations and Trends in Information Retrieval, 2(1-2), 1-135. DOI ↗ |
| Другие названия | DA, Critical Discourse Analysis, Discursive Analysis | opinion mining, polarity detection, duygu analizi |
| Связанные≠ | 2 | 3 |
| Сводка≠ | 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. | 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. |
| ScholarGateНабор данных ↗ |
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