Paper: Sentiment Learning on Product Reviews via Sentiment Ontology Tree

ACL ID P10-1042
Title Sentiment Learning on Product Reviews via Sentiment Ontology Tree
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2010
Authors

Existing works on sentiment analysis on product reviews suffer from the following limitations: (1) The knowledge of hierar- chical relationships of products attributes is not fully utilized. (2) Reviews or sen- tences mentioning several attributes asso- ciated with complicated sentiments are not dealt with very well. In this paper, we pro- pose a novel HL-SOT approach to label- ing a product’s attributes and their asso- ciated sentiments in product reviews by a Hierarchical Learning (HL) process with a defined Sentiment Ontology Tree (SOT). The empirical analysis against a human- labeled data set demonstrates promising and reasonable performance of the pro- posed HL-SOT approach. While this pa- per is mainly on sentiment analysis on re- views of one product, our proposed HL- SOT approach...