Recognizing Stances in Online Debates

This paper presents an unsupervised opinion analysis method for debate-side classification, i.e., recognizing which stance a person is taking in an online debate. In order to handle the complexities of this genre, we mine the web to learn associations that are indicative of opinion stances in debates. We combine this knowledge with discourse information, and formulate the debate side classification task as an Integer Linear Programming problem. Our results show that our method is substantially better than challenging baseline methods.

• Type: Journal
• Year: 2009
• Where: ACL
• Authors: Swapna Somasundaran, Janyce Wiebe
• Keywords: ACL 2009, Computational Linguistics, Integer Linear Programming, Opinion Stances, Unsupervised Opinion Analysis