Disambiguating Sentiment Ambiguous Adjectives

This paper makes a systematic study on disambiguating sentiment ambiguous adjectives within context in real text, which is an interaction between word sense disambiguation and sentiment analysis. We firstly address the issue of inter-annotator agreement on assigning semantic orientations to word occurrences in real text. Secondly we demonstrate that co-occurring sentiment monosemous adjectives can not effectively disambiguate sentiment ambiguous adjectives. Then collocation-based disambiguation and support vector machine (SVM) algorithm are exploited on the task of disambiguation. We present a new approach of combining collocation information and SVM to disambiguate sentiment ambiguous words. The experimental results show that the combining approach of Coll+SVM outperforms both collocation-based method and SVM algorithm.