Not-NUTs at W-NUT 2020 Task 2: A BERT-based System in Identifying Informative COVID-19 English Tweets

• URL: http://arxiv.org/abs/2009.06372v1
• Date: Mon, 14 Sep 2020 15:49:16 GMT
• Title: Not-NUTs at W-NUT 2020 Task 2: A BERT-based System in Identifying Informative COVID-19 English Tweets
• Authors: Thai Quoc Hoang and Phuong Thu Vu
• Abstract summary: We propose a model that, given an English tweet, automatically identifies whether that tweet bears informative content regarding COVID-19 or not. We have achieved competitive results that are only shy of those by top performing teams by roughly 1% in terms of F1 score on the informative class.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: As of 2020 when the COVID-19 pandemic is full-blown on a global scale, people's need to have access to legitimate information regarding COVID-19 is more urgent than ever, especially via online media where the abundance of irrelevant information overshadows the more informative ones. In response to such, we proposed a model that, given an English tweet, automatically identifies whether that tweet bears informative content regarding COVID-19 or not. By ensembling different BERTweet model configurations, we have achieved competitive results that are only shy of those by top performing teams by roughly 1% in terms of F1 score on the informative class. In the post-competition period, we have also experimented with various other approaches that potentially boost generalization to a new dataset.

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