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Change of Perspective.

Photo: Paderborn University

Timon Gurcke

Contact
Publications
 Timon Gurcke

Computational Social Science

Research Associate

Office:
ZM2.A.03.04
Visitor:
Zukunftsmeile 2
33102 Paderborn

Open list in Research Information System

2021

Key Point Analysis via Contrastive Learning and Extractive Argument Summarization

M. Alshomary, T. Gurcke, S. Syed, P. Heinisch, M. Spliethöver, P. Cimiano, M. Potthast, H. Wachsmuth, in: Proceedings of the 8th Workshop on Argument Mining, 2021


Belief-based Generation of Argumentative Claims

M. Alshomary, W. Chen, T. Gurcke, H. Wachsmuth, in: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, Association for Computational Linguistics, 2021, pp. 224-223

When engaging in argumentative discourse, skilled human debaters tailor claims to the beliefs of the audience, to construct effective arguments. Recently, the field of computational argumentation witnessed extensive effort to address the automatic generation of arguments. However, existing approaches do not perform any audience-specific adaptation. In this work, we aim to bridge this gap by studying the task of belief-based claim generation: Given a controversial topic and a set of beliefs, generate an argumentative claim tailored to the beliefs. To tackle this task, we model the people's prior beliefs through their stances on controversial topics and extend state-of-the-art text generation models to generate claims conditioned on the beliefs. Our automatic evaluation confirms the ability of our approach to adapt claims to a set of given beliefs. In a manual study, we additionally evaluate the generated claims in terms of informativeness and their likelihood to be uttered by someone with a respective belief. Our results reveal the limitations of modeling users' beliefs based on their stances, but demonstrate the potential of encoding beliefs into argumentative texts, laying the ground for future exploration of audience reach.


    Assessing the Sufficiency of Arguments through Conclusion Generation

    T. Gurcke, M. Alshomary, H. Wachsmuth, in: Proceedings of the 8th Workshop on Argument Mining, 2021


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