Summarising the points made in online political debates

Charlie Egan; Advaith Siddharthan; Adam Wyner

Summarising the points made in online political debates

Charlie Egan
, Advaith Siddharthan
, Adam Wyner

Computing Science

Research output: Chapter in Book/Report/Conference proceeding › Published conference contribution

30 Citations (Scopus)

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 highperforming extractive summarizer.

Original language	English
Title of host publication	Proceedings of the Third Workshop on Argument Mining (ArgMining2016)
Publisher	ACL Anthology
Pages	134-143
Number of pages	10
ISBN (Electronic)	978-1-945626-17-3
Publication status	Published - 2016
Event	3rd Workshop on Argument Mining: ACL 2016 - Berlin, Germany Duration: 12 Aug 2016 → 12 Aug 2016 http://argmining2016.arg.tech/ (3rd Workshop on Argument Mining - ACL 2016)

Conference

Conference	3rd Workshop on Argument Mining
Abbreviated title	ArgMining 2016
Country/Territory	Germany
City	Berlin
Period	12/08/16 → 12/08/16
Internet address	http://argmining2016.arg.tech/ (3rd Workshop on Argument Mining - ACL 2016)

Bibliographical note

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

Access to Document

http://aclweb.org/anthology/W/W16/W16-2816.pdfLicence: CC BY

Cite this

@inproceedings{a118bb1c4ae54bb7992e2e4c8f870013,

title = "Summarising the points made in online political debates",

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 {\textquoteleft}point{\textquoteright} 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.",

author = "Charlie Egan and Advaith Siddharthan and Adam Wyner",

note = "This work was supported by the Economic and Social Research Council [Grant number ES/M001628/1].; 3rd Workshop on Argument Mining : ACL 2016, ArgMining 2016 ; Conference date: 12-08-2016 Through 12-08-2016",

year = "2016",

language = "English",

pages = "134--143",

booktitle = "Proceedings of the Third Workshop on Argument Mining (ArgMining2016)",

publisher = "ACL Anthology",

url = "http://argmining2016.arg.tech/",

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TY - GEN

T1 - Summarising the points made in online political debates

AU - Egan, Charlie

AU - Siddharthan, Advaith

AU - Wyner, Adam

N1 - This work was supported by the Economic and Social Research Council [Grant number ES/M001628/1].

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

M3 - Published conference contribution

SP - 134

EP - 143

BT - Proceedings of the Third Workshop on Argument Mining (ArgMining2016)

PB - ACL Anthology

T2 - 3rd Workshop on Argument Mining

Y2 - 12 August 2016 through 12 August 2016

ER -

Summarising the points made in online political debates

Abstract

Conference

Bibliographical note

Access to Document

Fingerprint

Cite this