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Detecção de Emoção em Texto×Análise de Frames×
ÁreaMineração de textoMineração de texto
FamíliaProcess / pipelineProcess / pipeline
Ano de origem19921982
Autor originalPaul Ekman (basic-emotions theory)Charles J. Fillmore
TipoNLP text-classification taskNLP frame-semantic parsing task
Fonte 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
Outros nomesemotion recognition, emotion classification, Duygu/His Tespiti (Emotion Detection)frame semantics, frame-semantic parsing, FrameNet analysis, Çerçeve Analizi (Frame Analysis) — NLP
Relacionados34
ResumoEmotion 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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ScholarGateComparar métodos: Emotion Detection · Frame Analysis. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare