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Will-they-won't-they: A very large dataset for stance detection on twitter

Published version
Peer-reviewed

Type

Conference Object

Change log

Authors

Conforti, C 
Berndt, J 
Pilehvar, MT 
Giannitsarou, Chryssi  ORCID logo  https://orcid.org/0000-0002-1488-2433

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.

Description

Keywords

Journal Title

Proceedings of the Annual Meeting of the Association for Computational Linguistics

Conference Name

58th Annual Meeting of the Association for Computational Linguistics

Journal ISSN

0736-587X

Volume Title

Publisher

Sponsorship
Keynes Fund, Cambridge