Fine granular aspect analysis using latent structural models

Meeting: 50th Annual Meeting of the Association for Computational Linguistics, Jeju, Republic of Korea, 8-14 July 2012In this paper, we present a structural learning model for joint sentiment classification and aspect analysis of text at various levels of granularity. Online reviews have become a major resource where users find opinions or comments on products or services they want to consume. Aspect level sentiment analysis may be useful for a more global picture of opinions on the product’s properties. The resulting model is able to predict the sentiment polarity of a document as well as to identify aspect-specific sentences. A machine-learning algorithm generalizes the Support Vector Machine (SVM) classifier