Sentiment identification by incorporating syntax, semantics and context information

Kunpeng Zhang, Yusheng Xie, Yu Cheng, Daniel Honbo, Doug Downey, Ankit Agrawal, Wei-keng Liao, Alok N. Choudhary

Abstract: This paper proposes a method based on conditional random fields to incorporate sentence structure (syntax and semantics) and context information to identify sentiments of sentences within a document. It also proposes and evaluates two different active learning strategies for labeling sentiment data. The experiments with the proposed approach demonstrate a 5-15% improvement in accuracy on Amazon customer reviews compared to existing supervised learning and rule-based methods.