Fine-grained contextual predictions for hard sentiment words

Abstract

We put forward the hypothesis that highaccuracy sentiment analysis is only possible if word senses with different polarity are accurately recognized. We provide 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.