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

October 16, 2020 ยท Declared Dead ยท ๐Ÿ› WNUT

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Authors Dat Quoc Nguyen, Thanh Vu, Afshin Rahimi, Mai Hoang Dao, Linh The Nguyen, Long Doan arXiv ID 2010.08232 Category cs.CL: Computation & Language Citations 76 Venue WNUT Last Checked 4 months ago
Abstract
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.
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