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Emotion Expression in Modern Literary Appreciation: An Emotion-Based Analysis

BACKGROUND: Modern literary appreciation seems to be reading literary works phenomenally. In fact, appreciation is not a general reading, which has an important difference from general reading. It is the identification and appreciation of literary works and a complex spiritual activity for people to...

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Detalles Bibliográficos
Autor principal: Li, Jingxia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9248757/
https://www.ncbi.nlm.nih.gov/pubmed/35783782
http://dx.doi.org/10.3389/fpsyg.2022.923482
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author Li, Jingxia
author_facet Li, Jingxia
author_sort Li, Jingxia
collection PubMed
description BACKGROUND: Modern literary appreciation seems to be reading literary works phenomenally. In fact, appreciation is not a general reading, which has an important difference from general reading. It is the identification and appreciation of literary works and a complex spiritual activity for people to feel, understand, and imagine literary and artistic works. At the same time, literary appreciation is also a cognitive activity, an aesthetic activity, and a re-creation activity. METHOD: In this paper, the machine learning algorithm was creatively used to classify the emotions of figures in modern literary works, to analyze the emotions of the figures that the writer wanted to depict in modern literary works. RESULTS: Experimental results verify the accuracy of the emotion classification method through experiments, which is helpful for us to better understand the emotion expression in modern literary works.
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spelling pubmed-92487572022-07-02 Emotion Expression in Modern Literary Appreciation: An Emotion-Based Analysis Li, Jingxia Front Psychol Psychology BACKGROUND: Modern literary appreciation seems to be reading literary works phenomenally. In fact, appreciation is not a general reading, which has an important difference from general reading. It is the identification and appreciation of literary works and a complex spiritual activity for people to feel, understand, and imagine literary and artistic works. At the same time, literary appreciation is also a cognitive activity, an aesthetic activity, and a re-creation activity. METHOD: In this paper, the machine learning algorithm was creatively used to classify the emotions of figures in modern literary works, to analyze the emotions of the figures that the writer wanted to depict in modern literary works. RESULTS: Experimental results verify the accuracy of the emotion classification method through experiments, which is helpful for us to better understand the emotion expression in modern literary works. Frontiers Media S.A. 2022-06-17 /pmc/articles/PMC9248757/ /pubmed/35783782 http://dx.doi.org/10.3389/fpsyg.2022.923482 Text en Copyright © 2022 Li. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Li, Jingxia
Emotion Expression in Modern Literary Appreciation: An Emotion-Based Analysis
title Emotion Expression in Modern Literary Appreciation: An Emotion-Based Analysis
title_full Emotion Expression in Modern Literary Appreciation: An Emotion-Based Analysis
title_fullStr Emotion Expression in Modern Literary Appreciation: An Emotion-Based Analysis
title_full_unstemmed Emotion Expression in Modern Literary Appreciation: An Emotion-Based Analysis
title_short Emotion Expression in Modern Literary Appreciation: An Emotion-Based Analysis
title_sort emotion expression in modern literary appreciation: an emotion-based analysis
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9248757/
https://www.ncbi.nlm.nih.gov/pubmed/35783782
http://dx.doi.org/10.3389/fpsyg.2022.923482
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