Chinese Psychological Counseling Corpus Construction for Valence-Arousal Sentiment Intensity Prediction

While several dimensional sentiment resources with valence-arousal annotations exist, they are not appropriate for domain-specific sentiment applications, especially psychological counseling texts which usually contain more high-negative and high-arousal words and phrases. This study (1) builds a Chinese valence-arousal resource in the psychological counseling domain called CVAT-PC, the first text corpus including 2,400 multi-sentence texts for psychological counseling with valence-arousal ratings manually annotated based on the Self-Assessment Manikin (SAM) rating scale, and (2) evaluates the proposed resource using different transformer-based models, including ELECTRA, XLNet, BERT, MacBERT and RoBERTa. We plan to release the entire CVAT-PC corpus with fully annotated valence-arousal ratings to facilitate future development in related research areas.

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Published
2024-10-17
DOI
https://doi.org/10.1109/o-cocosda64382.2024.10800036
Primary Topic
Sentiment Analysis and Opinion Mining
Type
article
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article

Chinese Psychological Counseling Corpus Construction for Valence-Arousal Sentiment Intensity Prediction

Tzu-Mi Lin, Kuo‐Kai Shyu, Y. C. Tzeng, Hsiu-Min Shih et al.
Sentiment Analysis and Opinion Mining
article

Chinese Psychological Counseling Corpus Construction for Valence-Arousal Sentiment Intensity Prediction

Tzu-Mi Lin, Kuo‐Kai Shyu, Y. C. Tzeng, Hsiu-Min Shih, Jung-Ying Chang, Lung‐Hao Lee
article en

Abstract

While several dimensional sentiment resources with valence-arousal annotations exist, they are not appropriate for domain-specific sentiment applications, especially psychological counseling texts which usually contain more high-negative and high-arousal words and phrases. This study (1) builds a Chinese valence-arousal resource in the psychological counseling domain called CVAT-PC, the first text corpus including 2,400 multi-sentence texts for psychological counseling with valence-arousal ratings manually annotated based on the Self-Assessment Manikin (SAM) rating scale, and (2) evaluates the proposed resource using different transformer-based models, including ELECTRA, XLNet, BERT, MacBERT and RoBERTa. We plan to release the entire CVAT-PC corpus with fully annotated valence-arousal ratings to facilitate future development in related research areas.

National Yang Ming Chiao Tung University (TW), National Central University (TW), Institute of Art (PL)
Gender equality
Openalex Percentile: Top 78%
Sentiment Analysis and Opinion Mining
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Chinese Psychological Counseling Corpus Construction for Valence-Arousal Sentiment Intensity Prediction — Tzu-Mi Lin, Kuo‐Kai Shyu, et al. · (2024) | TGRS Research Map | TGRS