Paper: Reranking Models in Fine-grained Opinion Analysis

ACL ID C10-1059
Title Reranking Models in Fine-grained Opinion Analysis
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2010
Authors

We describe the implementation of reranking models for fine-grained opinion analysis – marking up opinion expres- sions and extracting opinion holders. The reranking approach makes it possible to model complex relations between multiple opinions in a sentence, allowing us to represent how opinions interact through the syntactic and semantic structure. We carried out evaluations on the MPQA corpus, and the experiments showed significant improvements over a conventional system that only uses local information: for both tasks, our system saw recall boosts of over 10 points.