Summarising the points made in online political debates

Charlie Egan, Advaith Siddharthan, Adam Wyner

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution


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 highperforming extractive summarizer.
Original languageEnglish
Title of host publicationProceedings of the Third Workshop on Argument Mining (ArgMining2016)
PublisherACL Anthology
Number of pages10
ISBN (Electronic)978-1-945626-17-3
Publication statusPublished - 2016
Event3rd Workshop on Argument Mining: ACL 2016 - Berlin, Germany
Duration: 12 Aug 201612 Aug 2016 (3rd Workshop on Argument Mining - ACL 2016)


Conference3rd Workshop on Argument Mining
Abbreviated titleArgMining 2016
Internet address

Bibliographical note

This work was supported by the Economic and Social Research Council [Grant number ES/M001628/1].


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