Frame-oriented Summarization of Argumentative Discussions

authored by

Shahbaz Syed, Timon Ziegenbein, Philipp Heinisch, Henning Wachsmuth, Martin Potthast

Abstract

Online discussions on controversial topics with many participants frequently include hundreds of arguments that cover different framings of the topic. But these arguments and frames are often spread across the various branches of the discussion tree structure. This makes it difficult for interested participants to follow the discussion in its entirety as well as to introduce new arguments. In this paper, we present a new rank-based approach to extractive summarization of online discussions focusing on argumentation frames that capture the different aspects of a discussion. Our approach includes three retrieval tasks to find arguments in a discussion that are (1) relevant to a frame of interest, (2) relevant to the topic under discussion, and (3) informative to the reader. Based on a joint ranking by these three criteria for a set of user-selected frames, our approach allows readers to quickly access an ongoing discussion. We evaluate our approach using a test set of 100 controversial Reddit ChangeMyView discussions, for which the relevance of a total of 1871 arguments was manually annotated.

Organisation(s)

Natural Language Processing Section

External Organisation(s)

Leipzig University
Bielefeld University
Center for Scalable Data Analytics and Artificial Intelligence Dresden/Leipzig (ScaDS.AI)

Type

Conference contribution

Pages

114-129

Publication date

2023

Publication status

Published

Peer reviewed

Yes

Electronic version(s)

https://doi.org/10.18653/v1/2023.sigdial-1.10 (Access: Open)