Towards Automatic Argument Extraction and Visualization in a Deliberative Model of Online Consultations for Local Governments

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9809)

Abstract

Automatic extraction and visualization of arguments used in a long online discussion, especially if the discussion involves a large number of participants and spreads over several days, can be helpful to the people involved. The main benefit is that they do not have to read all entries to get to know the main topics being discussed and can refer to existing arguments instead of introducing them anew. Such discussions take place, i.e., on a deliberative platform being developed under the ‘In Dialogue’ project. In this paper we propose a framework allowing for automatic extraction of arguments from deliberations and visualization. The framework assumes extraction of arguments and argument proposals, sentiment analysis to predict whether argument is negative or positive, classification to decide how the arguments are related and the use of ontology for visualization.

Keywords

Automatic argumentation extraction Argumentation visualization Argument mining Natural language processing 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Institute of Computer ScienceWarsaw University of TechnologyWarsawPoland

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