Paper: Open Domain Targeted Sentiment

ACL ID D13-1171
Title Open Domain Targeted Sentiment
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013

We propose a novel approach to sentiment analysis for a low resource setting. The in- tuition behind this work is that sentiment expressed towards an entity, targeted senti- ment, may be viewed as a span of sentiment expressed across the entity. This represen- tation allows us to model sentiment detec- tion as a sequence tagging problem, jointly discovering people and organizations along with whether there is sentiment directed to- wards them. We compare performance in both Spanish and English on microblog data, using only a sentiment lexicon as an exter- nal resource. By leveraging linguistically- informed features within conditional random fields (CRFs) trained to minimize empiri- cal risk, our best models in Spanish signifi- cantly outperform a strong baseline, and reach around 90% accu...