@inproceedings{alshomary-etal-2022-moral,
title = "The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments",
author = "Alshomary, Milad and
El Baff, Roxanne and
Gurcke, Timon and
Wachsmuth, Henning",
editor = "Muresan, Smaranda and
Nakov, Preslav and
Villavicencio, Aline",
booktitle = "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = may,
year = "2022",
address = "Dublin, Ireland",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.acl-long.601",
doi = "10.18653/v1/2022.acl-long.601",
pages = "8782--8797",
abstract = "An audience{'}s prior beliefs and morals are strong indicators of how likely they will be affected by a given argument. Utilizing such knowledge can help focus on shared values to bring disagreeing parties towards agreement. In argumentation technology, however, this is barely exploited so far. This paper studies the feasibility of automatically generating morally framed arguments as well as their effect on different audiences. Following the moral foundation theory, we propose a system that effectively generates arguments focusing on different morals. In an in-depth user study, we ask liberals and conservatives to evaluate the impact of these arguments. Our results suggest that, particularly when prior beliefs are challenged, an audience becomes more affected by morally framed arguments.",
}
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%0 Conference Proceedings
%T The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments
%A Alshomary, Milad
%A El Baff, Roxanne
%A Gurcke, Timon
%A Wachsmuth, Henning
%Y Muresan, Smaranda
%Y Nakov, Preslav
%Y Villavicencio, Aline
%S Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F alshomary-etal-2022-moral
%X An audience’s prior beliefs and morals are strong indicators of how likely they will be affected by a given argument. Utilizing such knowledge can help focus on shared values to bring disagreeing parties towards agreement. In argumentation technology, however, this is barely exploited so far. This paper studies the feasibility of automatically generating morally framed arguments as well as their effect on different audiences. Following the moral foundation theory, we propose a system that effectively generates arguments focusing on different morals. In an in-depth user study, we ask liberals and conservatives to evaluate the impact of these arguments. Our results suggest that, particularly when prior beliefs are challenged, an audience becomes more affected by morally framed arguments.
%R 10.18653/v1/2022.acl-long.601
%U https://aclanthology.org/2022.acl-long.601
%U https://doi.org/10.18653/v1/2022.acl-long.601
%P 8782-8797
Markdown (Informal)
[The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments](https://aclanthology.org/2022.acl-long.601) (Alshomary et al., ACL 2022)
ACL