UIT-HSE at WNUT-2020 Task 2: Exploiting CT-BERT for Identifying COVID-19 Information on the Twitter Social Network
September 07, 2020 ยท Declared Dead ยท ๐ WNUT
"No code URL or promise found in abstract"
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Authors
Khiem Vinh Tran, Hao Phu Phan, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen
arXiv ID
2009.02935
Category
cs.CL: Computation & Language
Citations
8
Venue
WNUT
Last Checked
5 months ago
Abstract
Recently, COVID-19 has affected a variety of real-life aspects of the world and led to dreadful consequences. More and more tweets about COVID-19 has been shared publicly on Twitter. However, the plurality of those Tweets are uninformative, which is challenging to build automatic systems to detect the informative ones for useful AI applications. In this paper, we present our results at the W-NUT 2020 Shared Task 2: Identification of Informative COVID-19 English Tweets. In particular, we propose our simple but effective approach using the transformer-based models based on COVID-Twitter-BERT (CT-BERT) with different fine-tuning techniques. As a result, we achieve the F1-Score of 90.94\% with the third place on the leaderboard of this task which attracted 56 submitted teams in total.
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