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A News Editorial Corpus for Mining Argumentation Strategies

机译:新闻编辑语料库的挖掘策略

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Many argumentative texts, and news editorials in particular, follow a specific strategy to persuade their readers of some opinion or attitude. This includes decisions such as when to tell an anecdote or where to support an assumption with statistics, which is reflected by the composition of different types of argumentative discourse units in a text. While several argument mining corpora have recently been published, they do not allow the study of argumentation strategies due to incomplete or coarse-grained unit annotations. This paper presents a novel corpus with 300 editorials from three diverse news portals that provides the basis for mining argumentation strategies. Each unit in all editorials has been assigned one of six types by three annotators with a high Fleiss' k agreement of 0.56. We investigate various challenges of the annotation process and we conduct a first corpus analysis. Our results reveal different strategies across the news portals, exemplifying the benefit of studying editorials-a so far underresourced text genre in argument mining.
机译:许多有争议的文章,尤其是新闻社论,都遵循特定的策略说服读者一些意见或态度。这包括诸如何时讲轶事或在何处以统计支持假设的决定,这由文本中不同类型的论证话语单元的组成反映出来。尽管最近已发布了几种论证挖掘语料库,但由于单元注释不完整或粗粒度,它们不允许研究论证策略。本文介绍了一个新颖的语料库,它具有来自三个不同新闻门户的300篇社论,为挖掘论证策略提供了基础。由三位注释者将所有社论中的每个单元分配为六种类型之一,其Fleiss k值为0.56。我们调查注释过程的各种挑战,并进行首次语料库分析。我们的结果揭示了整个新闻门户网站的不同策略,证明了研究社论的好处-迄今为止,在论点挖掘中资源匮乏的文本体裁。

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