Paper: Fine-Grained Contextual Predictions for Hard Sentiment Words

ACL ID D14-1128
Title Fine-Grained Contextual Predictions for Hard Sentiment Words
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014
Authors

We put forward the hypothesis that high- accuracy sentiment analysis is only pos- sible if word senses with different polar- ity are accurately recognized. We pro- vide evidence for this hypothesis in a case study for the adjective ?hard? and propose contextually enhanced sentiment lexicons that contain the information necessary for sentiment-relevant sense disambiguation. An experimental evaluation demonstrates that senses with different polarity can be distinguished well using a combination of standard and novel features.