SMM4H 2022 Task 2: Dataset for stance and premise detection in tweets about health mandates related to COVID-19
2022-10-01SMM4H (COLING) 2022Unverified0· sign in to hype
Vera Davydova, Elena Tutubalina
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This paper is an organizers’ report of the competition on argument mining systems dealing with English tweets about COVID-19 health mandates. This competition was held within the framework of the SMM4H 2022 shared tasks. During the competition, the participants were offered two subtasks: stance detection and premise classification. We present a manually annotated corpus containing 6,156 short posts from Twitter on three topics related to the COVID-19 pandemic: school closures, stay-at-home orders, and wearing masks. We hope the prepared dataset will support further research on argument mining in the health field.