Sentiment Propagation via Implicature Constraints
Lingjia Deng, Janyce Wiebe · 2014
Opinions may be expressed implicitly via inference over explicit sentiments and events that positively/negatively affect entities (goodFor/badFor events).We investigate how such inferences may be exploited to improve sentiment analysis, given goodFor/badFor event information.We apply Loopy Belief Propagation to propagate sentiments among entities.The graph-based model improves over explicit sentiment classification by 10 points in precision and, in an evaluation of the model itself, we find it has an 89% chance of propagating sentiments correctly.