Paper: Frame Semantics for Stance Classification

ACL ID W13-3514
Title Frame Semantics for Stance Classification
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2013
Authors

Determining the stance expressed by an author from a post written for a two-sided debate in an online debate forum is a relatively new problem in opinion min- ing. We extend a state-of-the-art learning- based approach to debate stance classifica- tion by (1) inducing lexico-syntactic pat- terns based on syntactic dependencies and semantic frames that aim to capture the meaning of a sentence and provide a gen- eralized representation of it; and (2) im- proving the classification of a test post via a novel way of exploiting the information in other test posts with the same stance. Empirical results on four datasets demon- strate the effectiveness of our extensions.