mlsanityData to 14 Oct 2026

WNUT-2020 Task 2: Identification of Informative COVID-19 English Tweets

arXiv 2010.08232 ↗First posted 16 Oct 2020cs.CLcited by 10

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Abstract (arXiv)

In this paper, we provide an overview of the WNUT-2020 shared task on the identification of informative COVID-19 English Tweets. We describe how we construct a corpus of 10K Tweets and organize the development and evaluation phases for this task. In addition, we also present a brief summary of results obtained from the final system evaluation submissions of 55 teams, finding that (i) many systems obtain very high performance, up to 0.91 F1 score, (ii) the majority of the submissions achieve substantially higher results than the baseline fastText (Joulin et al., 2017), and (iii) fine-tuning pre-trained language models on relevant language data followed by supervised training performs well in this task.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). First posted on arXiv 16 Oct 2020.

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Citing papers per year: 2021: 3; 2022: 1; 2023: 2; 2024: 3; 2025: 1.

10 papers.