Paper: Learning Extraction Patterns For Subjective Expressions

ACL ID W03-1014
Title Learning Extraction Patterns For Subjective Expressions
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2003
Authors

This paper presents a bootstrapping process that learns linguistically rich extraction pat- terns for subjective (opinionated) expressions. High-precision classifiers label unannotated data to automatically create a large training set, which is then given to an extraction pattern learning algorithm. The learned patterns are then used to identify more subjective sentences. The bootstrapping process learns many subjec- tive patterns and increases recall while main- taining high precision.