Will-They-Won't-They: A Very Large Dataset for Stance Detection on Twitter
Costanza Conforti, Jakob Berndt, Mohammad Taher Pilehvar, Chryssi Giannitsarou, Flavio Toxvaerd, Nigel Collier
Resources and Evaluation Short Paper
Session 2B: Jul 6
(09:00-10:00 GMT)
Session 3A: Jul 6
(12:00-13:00 GMT)
Abstract:
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.
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