Many computational argumentation tasks, like stance classification, are
topic-dependent: the effectiveness of approaches to these tasks significantly
depends on whether the approaches were trained on arguments from the same
topics as those they are tested on. So, which are these topics that researchers
train approaches on? This paper contributes the first comprehensive survey of
topic coverage, assessing 45 argument corpora. For the assessment, we take the
first step towards building an argument topic ontology, consulting three
diverse authoritative sources: the World Economic Forum, the Wikipedia list of
controversial topics, and Debatepedia. Comparing the topic sets between the
authoritative sources and corpora, our analysis shows that the corpora
topics-which are mostly those frequently discussed in public online fora - are
covered well by the sources. However, other topics from the sources are less
extensively covered by the corpora of today, revealing interesting future
directions for corpus construction.

该论文通过第一次全面调查话题覆盖范围，从三个权威来源比较话题集合，找出语料库与其频繁讨论的话题重合度最高，发现大多数语料库覆盖公共在线论坛上经常讨论的话题。但是，这些语料库还没有涵盖来自权威来源的其他话题，揭示了未来语料库建设的有趣方向。