Improving Multi-Label Emotion Classification on Imbalanced Social Media Data With BERT and Clipped Asymmetric Loss
This research addresses the challenge of multi-label emotion classification on imbalanced datasets using a BERT-based model. Emotion classification, essential for applications like social media analysis and sentiment monitoring, often suffers from class imbalance, which hinders the detection of rare...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10947681/ |
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