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Faculty of Economics

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Conforti, C., Berndt, J., Pilehvar, M. T., Giannitsarou, C., Toxvaerd, F. and Collier, N.

Will-They-Won’t-They: A Very Large Dataset for Stance Detection on Twitter

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

pp. 1715-1724 (2020)

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.

Author links: Chryssi Giannitsarou  Flavio Toxvaerd  

Publisher's Link: http://dx.doi.org/10.18653/v1/2020.acl-main.157

Keynes Fund Project(s):
Mapping of Rumours and Information Diffusion (JHOQ)  



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