DeepAI
Log In Sign Up

WNUT-2020 Task 2: Identification of Informative COVID-19 English Tweets

10/16/2020
by   Dat Quoc Nguyen, et al.
5

In this paper, we provide an overview of the WNUT-2020 shared task on the identification of informative COVID-19 English Tweets. We describe how we construct a corpus of 10K Tweets and organize the development and evaluation phases for this task. In addition, we also present a brief summary of results obtained from the final system evaluation submissions of 55 teams, finding that (i) many systems obtain very high performance, up to 0.91 F1 score, (ii) the majority of the submissions achieve substantially higher results than the baseline fastText (Joulin et al., 2017), and (iii) fine-tuning pre-trained language models on relevant language data followed by supervised training performs well in this task.

READ FULL TEXT

page 1

page 2

page 3

page 4

07/14/2022

Overview of Abusive and Threatening Language Detection in Urdu at FIRE 2021

With the growth of social media platform influence, the effect of their ...
11/11/2020

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...
09/14/2020

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...
04/22/2018

IIIDYT at SemEval-2018 Task 3: Irony detection in English tweets

In this paper we introduce our system for the task of Irony detection in...