The Psychology of Semantic Spaces: Experiments with Positive Emotion (Student Abstract)

被引:0
|
作者
Liu, Xuan [1 ]
Jaidka, Kokil [2 ]
Chhaya, Niyati [3 ]
机构
[1] Univ Calif Berkeley, Berkeley, CA 94720 USA
[2] Natl Univ Singapore, Singapore, Singapore
[3] Adobe Res, Bengaluru, Karnataka, India
来源
THIRTY-SIXTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FOURTH CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE / TWELVETH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE | 2022年
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Psychological concepts can help computational linguists to better model the latent semantic spaces of emotions, and understand the underlying states motivating the sharing or suppressing of emotions. This abstract applies the understanding of agency and social interaction in the happiness semantic space to its role in positive emotion. BERT-based fine-tuning yields an expanded seed set to understand the vocabulary of the latent space. Results benchmarked against many emotion datasets suggest that the approach is valid, robust, offers an improvement over direct prediction, and is useful for downstream predictive tasks related to psychological states.
引用
收藏
页码:13007 / 13008
页数:2
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