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

ACL ID P10-1043
Title Employing Personal/Impersonal Views in Supervised and Semi-Supervised Sentiment Classification
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2010
Authors

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.