Employing Personal/Impersonal Views in Supervised and Semi-Supervised Sentiment Classification

In this paper, we adopt two views, personal and impersonal views, and systematically employ them in both supervised and semi-supervised sentiment classification. Here, personal views consist of those sentences which directly express speaker's feeling and preference towards a target object while impersonal views focus on statements towards a target object for evaluation. To obtain them, an unsupervised mining approach is proposed. On this basis, an ensemble method and a co-training algorithm are explored to employ the two views in supervised and semi-supervised sentiment classification respectively. Experimental results across eight domains demonstrate the effectiveness of our proposed approach.

• Type: Journal
• Year: 2010
• Where: ACL
• Authors: Shoushan Li, Chu-Ren Huang, Guodong Zhou, Sophia Yat Mei Lee
• Keywords: ACL 2010, Computational Linguistics, Impersonal Views, Sentiment Classification, Target Object