Modeling Frames in Argumentation

Yamen Ajjour, Milad Alshomary, Henning Wachsmuth, Benno Stein
2019 Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)  
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
more » ... it 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 debateportal arguments, organized along the frames of the debates' topics. On this corpus, our approach outperforms different strong baselines, achieving an F 1 -score of 0.28.
doi:10.18653/v1/d19-1290 dblp:conf/emnlp/AjjourAWS19 fatcat:mm6dsgmlerd6bjjydwkmy3p3pu