LynyrdSkynyrd at WNUT-2020 Task 2: Semi-Supervised Learning for Identification of Informative COVID-19 English Tweets
September 08, 2020 ยท Declared Dead ยท ๐ WNUT
"No code URL or promise found in abstract"
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Authors
Abhilasha Sancheti, Kushal Chawla, Gaurav Verma
arXiv ID
2009.03849
Category
cs.CL: Computation & Language
Cross-listed
cs.SI
Citations
3
Venue
WNUT
Last Checked
5 months ago
Abstract
We describe our system for WNUT-2020 shared task on the identification of informative COVID-19 English tweets. Our system is an ensemble of various machine learning methods, leveraging both traditional feature-based classifiers as well as recent advances in pre-trained language models that help in capturing the syntactic, semantic, and contextual features from the tweets. We further employ pseudo-labelling to incorporate the unlabelled Twitter data released on the pandemic. Our best performing model achieves an F1-score of 0.9179 on the provided validation set and 0.8805 on the blind test-set.
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