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Egan, Charlie; Siddharthan, Advaith and Wyner, Adam
(2016).
URL: http://www.aclweb.org/anthology/W16-2816
Abstract
Online communities host growing numbers of discussions amongst large groups of participants on all manner of topics. This user-generated content contains millions of statements of opinions and ideas. We propose an abstractive approach to summarize such argumentative discussions, making key content accessible through ‘point’ extraction, where a point is a verb and its syntactic arguments. Our approach uses both dependency parse information and verb case frames to identify and extract valid points, and generates an abstractive summary that discusses the key points being made in the debate. We performed a human evaluation of our approach using a corpus of online political debates and report significant improvements over a high-performing extractive summarizer.
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- Item ORO ID
- 58723
- Item Type
- Conference or Workshop Item
- ISBN
- 1-945626-17-8, 978-1-945626-17-3
- Academic Unit or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Copyright Holders
- © 2016 Association for Computational Linguistics
- Depositing User
- Advaith Siddharthan