Minimally Supervised Learning of Affective Events Using Discourse Relations (D19-1)
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| Challenge: | Existing methods for learning affective events that trigger positive or negative sentiment are difficult because of the unbounded combinatorial nature of language. |
| Approach: | They propose to propagate affective polarity using discourse relations using a small seed lexicon and large raw corpus. |
| Outcome: | The proposed method learns affective events effectively without manually labeled data, and improves supervised learning when labeles are small. |
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