Identifying Prominent Arguments in Online Debates Using Semantic Textual Similarity
Filip Boltužić, Jan Šnajder · 2015
Online debates sparkle argumentative discussions from which generally accepted arguments often emerge.We consider the task of unsupervised identification of prominent argument in online debates.As a first step, in this paper we perform a cluster analysis using semantic textual similarity to detect similar arguments.We perform a preliminary cluster evaluation and error analysis based on cluster-class matching against a manually labeled dataset.