Papers with Limbic
Limbic: Author-Based Sentiment Aspect Modeling Regularized with Word Embeddings and Discourse Relations (D18-1)
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| Challenge: | Existing models for finding aspects and sentiments in opinionated texts ignore sentiments and are not supervised. |
| Approach: | They propose a probabilistic model that finds aspects and sentiments in opinionated texts . they use authors, discourse relations, and word embeddings to capture regularities . |
| Outcome: | The proposed model outperforms state-of-the-art models in topic cohesion and sentiment classification. |