Computational Models of Argument : Proceedings of COMMA 2016

Argument Mining using Argumentation Scheme Structures

Argumentation schemes are patterns of human reasoning which have been detailed extensively in philosophy and psychology. In this paper we demonstrate that the structure of such schemes can provide rich information to the task of automatically identify complex argumentative structures in natural language text. By training a range of classifiers to identify the individual proposition types which occur in these schemes, it is possible not only to determine where a scheme is being used, but also the roles played by its component parts. Furthermore, this task can be performed on segmented natural language, with no prior knowledge of the text's argumentative structure.

Lawrence J, Reed C A. (2016). Argument Mining using Argumentation Scheme Structures. In Computational Models of Argument : Proceedings of COMMA 2016 (Frontiers in artificial intelligence and applications ; v. 287) 379 -390. doi: 10.3233/978-1-61499-686-6-379