Paper: Clustering Aspect-related Phrases by Leveraging Sentiment Distribution Consistency

ACL ID D14-1169
Title Clustering Aspect-related Phrases by Leveraging Sentiment Distribution Consistency
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014
Authors

Clustering aspect-related phrases in terms of product?s property is a precursor pro- cess to aspect-level sentiment analysis which is a central task in sentiment analy- sis. Most of existing methods for address- ing this problem are context-based models which assume that domain synonymous phrases share similar co-occurrence con- texts. In this paper, we explore a novel idea, sentiment distribution consistency, which states that different phrases (e.g. ?price?, ?money?, ?worth?, and ?cost?) of the same aspect tend to have consistent sentiment distribution. Through formal- izing sentiment distribution consistency as soft constraint, we propose a novel unsu- pervised model in the framework of Poste- rior Regularization (PR) to cluster aspect- related phrases. Experiments demonstrate that our ...