Overview of Touché 2020

Argument Retrieval

authored by

Alexander Bondarenko, Maik Fröbe, Meriem Beloucif, Lukas Gienapp, Yamen Ajjour, Alexander Panchenko, Chris Biemann, Benno Stein, Henning Wachsmuth, Martin Potthast, Matthias Hagen

Abstract

Argumentation is essential for opinion formation when it comes to debating on socially important topics as well as when making everyday personal decisions. The web provides an enormous source of argumentative texts, where well-reasoned argumentations are mixed with biased, faked, and populist ones. The research direction of developing argument retrieval technologies thus focuses not only retrieving relevant arguments for some argumentative information need, but also on retrieving arguments of a high quality. In this overview of the first shared task on argument retrieval at the CLEF 2020 Touché lab, we survey and evaluate 41 approaches submitted by 17 participating teams for two tasks: (1) retrieval of arguments on socially important topics, and (2) retrieval of arguments on everyday personal decisions. The most effective approaches submitted share some common techniques, such as query expansion, and taking argument quality into account. Still, the evaluation results show that only few of the submitted approaches (slightly) improve upon relatively simple argumentation-agnostic baselines—indicating that argument retrieval is in its infancy and meriting further research into this direction.

External Organisation(s)

Martin Luther University Halle-Wittenberg
Universität Hamburg
Leipzig University
Skolkovo Institute of Science and Technology
Bauhaus-Universität Weimar
Paderborn University

Type

Conference article

Journal

CEUR Workshop Proceedings

Volume

2696

No. of pages

22

ISSN

1613-0073

Publication date

2020

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Computer Science(all)

Electronic version(s)

https://ceur-ws.org/Vol-2696/paper_261.pdf (Access: Open)