Summarising the points made in online political debates

Egan, Charlie; Siddharthan, Advaith and Wyner, Adam (2016). Summarising the points made in online political debates. In: Proceedings of the 3rd Workshop on Argument Mining, The 54th Annual Meeting of the Association for Computational Linguistics, Association for Computational Linguistics (ACL), Stroudsburg, PA pp. 134–143.



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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