Using Complex Argumentative Interactions to Reconstruct the Argumentative Structure of Large-Scale Debates

John Lawrence, Chris Reed


Abstract
In this paper we consider the insights that can be gained by considering large scale argument networks and the complex interactions between their constituent propositions. We investigate metrics for analysing properties of these networks, illustrating these using a corpus of arguments taken from the 2016 US Presidential Debates. We present techniques for determining these features directly from natural language text and show that there is a strong correlation between these automatically identified features and the argumentative structure contained within the text. Finally, we combine these metrics with argument mining techniques and show how the identification of argumentative relations can be improved by considering the larger context in which they occur.
Anthology ID:
W17-5114
Volume:
Proceedings of the 4th Workshop on Argument Mining
Month:
September
Year:
2017
Address:
Copenhagen, Denmark
Venues:
ArgMining | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
108–117
Language:
URL:
https://aclanthology.org/W17-5114
DOI:
10.18653/v1/W17-5114
Bibkey:
Cite (ACL):
John Lawrence and Chris Reed. 2017. Using Complex Argumentative Interactions to Reconstruct the Argumentative Structure of Large-Scale Debates. In Proceedings of the 4th Workshop on Argument Mining, pages 108–117, Copenhagen, Denmark. Association for Computational Linguistics.
Cite (Informal):
Using Complex Argumentative Interactions to Reconstruct the Argumentative Structure of Large-Scale Debates (Lawrence & Reed, 2017)
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PDF:
https://aclanthology.org/W17-5114.pdf