Paper: A Hierarchical Classifier Applied to Multi-way Sentiment Detection

ACL ID C10-1008
Title A Hierarchical Classifier Applied to Multi-way Sentiment Detection
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2010
Authors

This paper considers the problem of document-level multi-way sentiment de- tection, proposing a hierarchical classifier algorithm that accounts for the inter-class similarity of tagged sentiment-bearing texts. This type of classifier also pro- vides a natural mechanism for reducing the feature space of the problem. Our re- sults show that this approach improves on state-of-the-art predictive performance for movie reviews with three-star and four- star ratings, while simultaneously reduc- ing training times and memory require- ments.