Recognizing stances in online debates
Published 1 January 2009Open access
Swapna Somasundaran, Janyce Wiebe
Citations301
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TL;DR
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, and shows that this method is substantially better than challenging baseline methods.
Abstract
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.
Keywords
Computer Science
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