ArgMine: A Framework for Argumentation Mining

The aim of argumentation mining is the automatic detection and identification of the argumentative structure contained within a piece of natural language text. In this paper we present the ArgMine Framework: an alignment of tools and processes that facilitate and partially automate argumentation mining research. We also report on a preliminary exploitation of the framework, where we address argumentative zoning, a sub-task of argumentation mining, whose aim is to automatically select the zones of the text that contain argumentative content. The target corpus used to train the supervised machine learning algorithms was manually annotated and is composed of Portuguese news articles, to which argumentation mining does not seem to have been applied before. Given the dataset used in our experiments and from the critical analysis of the obtained results, we conclude that lexical and syntactic-based features are not enough to successfully address argumentation zoning.