Topic-Related Polarity Classification of Blog Sentences

Though polarity classification has been extensively explored at various text levels and domains, there has been only comparatively little work looking into topic-related polarity classification. This paper takes a detailed look at how sentences expressing a polar attitude towards a given topic can be retrieved from a blog collection. A cascade of independent text classifiers on top of a sentence-retrieval engine is a solution with limited effectiveness. We show that more sophisticated processing is necessary. In this context, we not only investigate the impact of a more precise detection and disambiguation of polar expressions beyond simple text classification but also inspect the usefulness of a joint analysis of topic terms and polar expressions. In particular, we examine whether any syntactic information is beneficial in this classification task.

• Type: Conference
• Year: 2009
• Where: EPIA
• Authors: Michael Wiegand, Dietrich Klakow
• Keywords: Artificial Intelligence, EPIA 2009, Polar Expressions, Polarity Classification, Topic-related Polarity Classification