Log In Sign Up

BANANA at WNUT-2020 Task 2: Identifying COVID-19 Information on Twitter by Combining Deep Learning and Transfer Learning Models

by   Tin Van Huynh, et al.

The outbreak COVID-19 virus caused a significant impact on the health of people all over the world. Therefore, it is essential to have a piece of constant and accurate information about the disease with everyone. This paper describes our prediction system for WNUT-2020 Task 2: Identification of Informative COVID-19 English Tweets. The dataset for this task contains size 10,000 tweets in English labeled by humans. The ensemble model from our three transformer and deep learning models is used for the final prediction. The experimental result indicates that we have achieved F1 for the INFORMATIVE label on our systems at 88.81


NIT COVID-19 at WNUT-2020 Task 2: Deep Learning Model RoBERTa for Identify Informative COVID-19 English Tweets

This paper presents the model submitted by the NIT_COVID-19 team for ide...

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

As of 2020 when the COVID-19 pandemic is full-blown on a global scale, p...

InfoMiner at WNUT-2020 Task 2: Transformer-based Covid-19 Informative Tweet Extraction

Identifying informative tweets is an important step when building inform...

And the Winner is ...: Bayesian Twitter-based Prediction on 2016 U.S. Presidential Election

This paper describes a Naive-Bayesian predictive model for 2016 U.S. Pre...