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Sentiment annotations for 3827 simplified Chinese characters.
Peng, Cheng; Xu, Xu; Bao, Zhen.
Afiliación
  • Peng C; Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.
  • Xu X; Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China. xu2xu3@gmail.com.
  • Bao Z; Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.
Behav Res Methods ; 56(2): 651-666, 2024 Feb.
Article en En | MEDLINE | ID: mdl-36754941
Sentiment analysis in Chinese natural language processing has been largely based on words annotated with sentiment categories or scores. Characters, however, are the basic orthographic, phonological, and in most cases, semantic units in the Chinese language. This study collected sentiment annotations for 3827 characters. The ratings demonstrated high levels of reliability, and were validated through a comparison with the ratings of some characters' word equivalents reported in a previous norming study. Relations with other lexico-semantic variables and character processing efficiency were investigated. Furthermore, analyses of the association between constituent character valence and word valence revealed semantic compositionality and sentiment fusion characteristic of larger Chinese linguistic units. These ratings for characters, expanding current Chinese sentiment lexicons, can be utilized for the purposes of more precise stimuli assessment in research on Chinese character processing and more efficient sentiment analysis equipped with annotations of single-character words.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Semántica / Lenguaje Límite: Humans Idioma: En Revista: Behav Res Methods Asunto de la revista: CIENCIAS DO COMPORTAMENTO Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Semántica / Lenguaje Límite: Humans Idioma: En Revista: Behav Res Methods Asunto de la revista: CIENCIAS DO COMPORTAMENTO Año: 2024 Tipo del documento: Article País de afiliación: China