Modeling Frames in Argumentation

authored by

Yamen Ajjour, Milad Alshomary, Henning Wachsmuth, Benno Stein

Abstract

In argumentation, framing is used to emphasize a specific aspect of a controversial topic while concealing others. When discussing the legalization of drugs, for instance, its economical aspect may be emphasized. In general, we call a set of arguments that focus on the same aspect a frame. An argumentative text has to serve the “right” frame(s) to convince the audience to adopt the author's stance (e.g., being pro or con legalizing drugs). More specifically, an author has to choose frames that fit the audience's interests and cultural background. This paper introduces frame identification, which is the task of splitting a set of arguments into a set of non-overlapping frames. We present a fully unsupervised approach to this task, which first removes topical information from the arguments and then identifies frames using clustering. For evaluation purposes, we provide a corpus with 12 326 debate-portal arguments, organized along the frames of the debates' topics. On this corpus, our approach outperforms different strong baselines, achieving an F₁-score of 0.28.

External Organisation(s)

Bauhaus-Universität Weimar
Paderborn University

Type

Conference contribution

Pages

2922-2932

No. of pages

11

Publication date

11.2019

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Computational Theory and Mathematics, Computer Science Applications, Information Systems

Electronic version(s)

https://doi.org/10.18653/v1/D19-1290 (Access: Open)
https://www.aclweb.org/anthology/D19-1290 (Access: Unknown)