Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Дискурс-анализ× | Классификация текстов× | |
|---|---|---|
| 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 | Supervised NLP classification task |
| Основополагающий источник≠ | Fairclough, N. (1989). Language and power. Longman. link ↗ | Joachims, T. (1998). Text Categorization with Support Vector Machines: Learning with Many Relevant Features. ECML 1998. Lecture Notes in Computer Science, vol 1398. Springer. DOI ↗ |
| Другие названия≠ | DA, Critical Discourse Analysis, Discursive Analysis | text categorization, document classification, topic classification, metin sınıflandırma |
| Связанные≠ | 2 | 4 |
| 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. | Text classification, also called text categorization, is a supervised natural-language-processing task that automatically assigns documents to predefined categories. Building on the support-vector-machine approach to text categorization established by Joachims (1998) and consolidated in the text-mining literature by Aggarwal and Zhai (2012), it powers tasks such as spam detection and topic classification by learning from labelled examples. |
| ScholarGateНабор данных ↗ |
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