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Detecció d'emocions en text×Anàlisi de marcs×
CampMineria de textMineria de text
FamíliaProcess / pipelineProcess / pipeline
Any d'origen19921982
Autor originalPaul Ekman (basic-emotions theory)Charles J. Fillmore
TipusNLP text-classification taskNLP frame-semantic parsing task
Font seminalEkman, 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
Àliesemotion recognition, emotion classification, Duygu/His Tespiti (Emotion Detection)frame semantics, frame-semantic parsing, FrameNet analysis, Çerçeve Analizi (Frame Analysis) — NLP
Relacionats34
ResumEmotion 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.
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ScholarGateCompara mètodes: Emotion Detection · Frame Analysis. Recuperat el 2026-06-18 de https://scholargate.app/ca/compare