论文标题
威尔 - 他们不会 - 他们：一个非常大的数据集，可在Twitter上检测
Will-They-Won't-They: A Very Large Dataset for Stance Detection on Twitter
论文作者
论文摘要
我们提出了一个新的具有挑战性的立场检测数据集，称为Will-they't-they't-they't-wt），其中包含51,284条英语推文，使其成为该类型的最大可用数据集。所有注释均由专家进行；因此，数据集构成了在立场检测中未来研究的高质量和可靠的基准。我们对广泛的最新立场检测系统进行的实验表明，该数据集对该域中的现有模型构成了巨大的挑战。
We present a new challenging stance detection dataset, called Will-They-Won't-They (WT-WT), which contains 51,284 tweets in English, making it by far the largest available dataset of the type. All the annotations are carried out by experts; therefore, the dataset constitutes a high-quality and reliable benchmark for future research in stance detection. Our experiments with a wide range of recent state-of-the-art stance detection systems show that the dataset poses a strong challenge to existing models in this domain.
