Paper: Multi-Level Structured Models for Document-Level Sentiment Classification

ACL ID D10-1102
Title Multi-Level Structured Models for Document-Level Sentiment Classification
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2010
Authors

In this paper, we investigate structured mod- els for document-level sentiment classifica- tion. When predicting the sentiment of a sub- jective document (e.g., as positive or nega- tive), it is well known that not all sentences are equally discriminative or informative. But identifying the useful sentences automatically is itself a difficult learning problem. This pa- per proposes a joint two-level approach for document-level sentiment classification that simultaneously extracts useful (i.e., subjec- tive) sentences and predicts document-level sentiment based on the extracted sentences. Unlike previous joint learning methods for the task, our approach (1) does not rely on gold standard sentence-level subjectivity an- notations (which may be expensive to obtain), and (2) optimizes directly...