LynyrdSkynyrd at WNUT-2020 Task 2: Semi-Supervised Learning for Identification of Informative COVID-19 English Tweets
Year: 2020
Type: conference-paper
Abstract: In this work, 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.
Authors: Abhilasha Sancheti, Kushal Chawla, Gaurav Verma
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W3084307218