Paper: Feature Subsumption For Opinion Analysis

ACL ID W06-1652
Title Feature Subsumption For Opinion Analysis
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2006
Authors

Lexical features are key to many ap- proaches to sentiment analysis and opin- ion detection. A variety of representations have been used, including single words, multi-word Ngrams, phrases, and lexico- syntactic patterns. In this paper, we use a subsumption hierarchy to formally de ne different types of lexical features and their relationship to one another, both in terms of representational coverage and perfor- mance. We use the subsumption hierar- chy in two ways: (1) as an analytic tool to automatically identify complex features that outperform simpler features, and (2) to reduce a feature set by removing un- necessary features. We show that reduc- ing the feature set improves performance on three opinion classi cation tasks, espe- cially when combined with traditional fea- ture selecti...