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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 2 of 2 1 Will-They-Won't-They: A Very Large Dataset for Stance Detection on Twitter ... Conforti, Costanza; Berndt, Jakob; Pilehvar, Mohammad Taher; Giannitsarou, Chryssi; Toxvaerd, Flavio; Collier, Nigel; Linguist, Assoc Computat. - : Apollo - University of Cambridge Repository, 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. ... : Keynes Fund, Cambridge ... URL: https://dx.doi.org/10.17863/cam.55294 https://www.repository.cam.ac.uk/handle/1810/308201 BASE Hide details 2 Will-They-Won't-They: A Very Large Dataset for Stance Detection on Twitter Conforti, Costanza; Berndt, Jakob; Pilehvar, Mohammad Taher. - : 58TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2020), 2020 BASE Show details

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