Comparer des méthodes

	Détection de propagande	Classification de texte
Domaine	Fouille de textes	Fouille de textes
Famille	Process / pipeline	Process / pipeline
Année d'origine	—	—
Auteur d'origine	—	—
Type	NLP text-classification task	Supervised NLP classification task
Source fondatrice	Da San Martino, G. et al. (2019). Fine-Grained Analysis of Propaganda in News Articles. EMNLP.	Joachims, T. (1998). Text Categorization with Support Vector Machines: Learning with Many Relevant Features. ECML 1998. Lecture Notes in Computer Science, vol 1398. Springer.
Alias	propaganda and manipulation detection, propaganda technique detection, Propaganda ve Manipülasyon Tespiti	text categorization, document classification, topic classification, metin sınıflandırma
Apparentées	4	4
Résumé	Propaganda detection is a natural-language-processing task that automatically identifies and labels persuasion and manipulation techniques in text — such as loaded language, oversimplified solutions, bandwagon appeals, and glittering generalities. It builds on the fine-grained propaganda analysis introduced by Da San Martino et al. (2019), turning rhetorical manipulation into structured, technique-level labels.	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.