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Applying Machine Learning Classifiers in Argumentation Context

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Distributed Computing and Artificial Intelligence, 17th International Conference (DCAI 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1237))

Abstract

Group decision making is an area that has been studied over the years. Group Decision Support Systems emerged with the aim of supporting decision makers in group decision-making processes. In order to properly support decision-makers these days, it is essential that GDSS provide mechanisms to properly support decision-makers. The application of Machine Learning techniques in the context of argumentation has grown over the past few years. Arguing includes negotiating arguments for and against a certain point of view. From political debates to social media posts, ideas are discussed in the form of an exchange of arguments. During the last years, the automatic detection of this arguments has been studied and it’s called Argument Mining. Recent advances in this field of research have shown that it is possible to extract arguments from unstructured texts and classifying the relations between them.

In this work, we used machine learning classifiers to automatically classify the direction (relation) between two arguments.

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Acknowledgments

This work was supported by National Funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within the Projects UIDB/00319/2020, UIDB/00760/2020, GrouPlanner Project (POCI-01-0145-FEDER-29178) and by the Luís Conceição Ph.D. Grant with the reference SFRH/BD/137150/2018.

Author information

Authors and Affiliations

  1. ALGORITMI Centre, University of Minho, 4800-058, Guimarães, Portugal

    Luís Conceição & Paulo Novais

  2. GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Institute of Engineering, Polytechnic of Porto, 4200-072, Porto, Portugal

    Luís Conceição, João Carneiro & Goreti Marreiros

Authors
  1. Luís Conceição
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  2. João Carneiro
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  3. Goreti Marreiros
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  4. Paulo Novais
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Corresponding author

Correspondence to Luís Conceição .

Editor information

Editors and Affiliations

  1. Business School, Sichuan University, Chengdu, China

    Yucheng Dong

  2. Andalusian Research Institute on Data Science and Computational Intelligence (DaSCI), University of Granada, Granada, Spain

    Enrique Herrera-Viedma

  3. Dept. of System Design, Osaka Institute of Technology, Osaka, Japan

    Kenji Matsui

  4. Hiroshima University, Osaka, Japan

    Shigeru Omatsu

  5. GRASIA Research Group, Facultad de Informática, Universidad Complutense de Madrid, Madrid, Spain

    Alfonso González Briones

  6. IoT European Digital Innovation Hub, Bioinformatics Intelligent Systems and Educational Technology Research Group, Department of Computer Science, Faculty of Science, University of Salamanca, Salamanca, Spain

    Sara Rodríguez González

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Conceição, L., Carneiro, J., Marreiros, G., Novais, P. (2021). Applying Machine Learning Classifiers in Argumentation Context. In: Dong, Y., Herrera-Viedma, E., Matsui, K., Omatsu, S., González Briones, A., Rodríguez González, S. (eds) Distributed Computing and Artificial Intelligence, 17th International Conference. DCAI 2020. Advances in Intelligent Systems and Computing, vol 1237. Springer, Cham. https://doi.org/10.1007/978-3-030-53036-5_34

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