विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| प्रचार का पता लगाना× | पाठ में भावना का पता लगाना× | फ़्रेम विश्लेषण× | |
|---|---|---|---|
| क्षेत्र | पाठ खनन | पाठ खनन | पाठ खनन |
| परिवार | Process / pipeline | Process / pipeline | Process / pipeline |
| उद्भव वर्ष≠ | — | 1992 | 1982 |
| प्रवर्तक≠ | — | Paul Ekman (basic-emotions theory) | Charles J. Fillmore |
| प्रकार≠ | NLP text-classification task | NLP text-classification task | NLP frame-semantic parsing task |
| मौलिक स्रोत≠ | Da San Martino, G. et al. (2019). Fine-Grained Analysis of Propaganda in News Articles. EMNLP. DOI ↗ | Ekman, P. (1992). An Argument for Basic Emotions. Cognition & Emotion, 6(3-4), 169-200. DOI ↗ | Fillmore, C. J. (1982). Frame Semantics. In Linguistics in the Morning Calm. Seoul: Hanshin Publishing. ISBN: 9788970050355 |
| उपनाम≠ | propaganda and manipulation detection, propaganda technique detection, Propaganda ve Manipülasyon Tespiti | emotion recognition, emotion classification, Duygu/His Tespiti (Emotion Detection) | frame semantics, frame-semantic parsing, FrameNet analysis, Çerçeve Analizi (Frame Analysis) — NLP |
| संबंधित≠ | 4 | 3 | 4 |
| सारांश≠ | 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. | Emotion detection is a natural-language-processing task that classifies the basic and complex emotions expressed in text — fear, joy, anger, sadness, surprise, and disgust — within a recognised emotion framework such as Ekman's basic-emotions model or Plutchik's wheel. It builds on Paul Ekman's 1992 argument for a small set of universal basic emotions, going beyond a simple positive/negative split to attach a specific emotion label to each piece of text. | Frame analysis is a FrameNet-based natural-language-processing task that detects the semantic frames evoked in text and the participant roles (frame-evoking elements and frame elements, FE) that fill them. Rooted in Charles Fillmore's frame semantics (1982) and operationalised by the Berkeley FrameNet Project (Baker et al., 1998), it is widely used to analyse media discourse and political text. |
| ScholarGateडेटासेट ↗ |
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