Data-driven weakly supervised emotion classification with consistency regularization: Mandarin Chinese as a case.

Emotion classification from text is a crucial task in affective computing, with applications in social informatics, human-computer interaction, and urban data analysis. This task involves identifying emotional states and answering questions such as, "Is the writer or reader happy, angry, or fearful...

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Detalles Bibliográficos

Publicado en:	Language Resources & Evaluation Vol. 59; no. 4; pp. 3975 - 4003
Autores principales:	Odbal, Zheng, Zhong, Zhang, Guanhong
Formato:	Artículo
Publicado:	Springer Nature Dec2025
Materias:	Emotion recognition Affective computing Machine learning Content analysis Supervised learning Artificial neural networks Mandarin dialects
Acceso en línea:	Ver este registro en EBSCOhost