Mining Arguments From 19th Century Philosophical Texts Using Topic Based Modelling

In Proceedings of the First Workshop on Argumentation Mining. Baltimore, USA: pp. 79-87 (2014)
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Abstract

In this paper we look at the manual analysis of arguments and how this compares to the current state of automatic argument analysis. These considerations are used to develop a new approach combining a machine learning algorithm to extract propositions from text, with a topic model to determine argument structure. The results of this method are compared to a manual analysis.

Author Profiles

Colin Allen
University of Pittsburgh
David Bourget
University of Western Ontario
Andrew Ravenscroft
University of East London

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