Bilingual Sentiment Embeddings: Joint Projection of Sentiment Across Languages (P18-1)
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| Challenge: | Existing approaches to sentiment analysis in low-resource languages lack annotated corpora or do not capture sentiment information. |
| Approach: | They propose a model that represents sentiment in a source and target language without annotated corpus. |
| Outcome: | The proposed model outperforms state-of-the-art methods on four out of six setups and captures complementary information to machine translation. |
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| Challenge: | Existing methods for sentiment lexicon induction are limited to low-resource languages. |
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| Challenge: | Recent efforts to leverage multilingual datasets highlight potential of multilingual models that can perform well across various languages. |
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