Zero-shot Sentiment Analysis in Low-Resource Languages Using a Multilingual Sentiment Lexicon (2024.eacl-long)
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| Challenge: | Prior work extended multilingual models to other languages due to the unavailability of labeled and unlabeled training data. |
| Approach: | They use multilingual lexicons to enhance multilingual models capabilities in low-resource languages . they focus on zero-shot sentiment analysis tasks across 34 languages based on a single sentence . |
| Outcome: | The proposed model improves zero-shot performance across 34 languages without using any sentence-level sentiment data. |
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