Compară metode

	Detectarea propagandei	Clasificarea textului
Domeniu	Mineritul textelor	Mineritul textelor
Familie	Process / pipeline	Process / pipeline
Anul apariției	—	—
Autorul original	—	—
Tip	NLP text-classification task	Supervised NLP classification task
Sursa seminală	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.
Denumiri alternative	propaganda and manipulation detection, propaganda technique detection, Propaganda ve Manipülasyon Tespiti	text categorization, document classification, topic classification, metin sınıflandırma
Înrudite	4	4
Rezumat	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.