Extraction of Texters’ Explicit Emotion Expressions in Crisis Conversations (2026.findings-acl)
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| Challenge: | Existing methods for extracting present and past personal emotion expressions from text-based crisis conversations are lacking in clinically relevant areas. |
| Approach: | They propose a method for extracting present and past personal emotion expressions from text-based crisis conversations and train a transformer-based model that captures contextual distinctions between true personal emotion and other mentions. |
| Outcome: | The proposed method outperforms a regex and a model trained on real conversation data and achieves an F1 score of 0.856. |
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