InfoMiner at WNUT-2020 Task 2: Transformer-based Covid-19 Informative Tweet Extraction
Computation and Language
2020-10-13 v1 Machine Learning
Abstract
Identifying informative tweets is an important step when building information extraction systems based on social media. WNUT-2020 Task 2 was organised to recognise informative tweets from noise tweets. In this paper, we present our approach to tackle the task objective using transformers. Overall, our approach achieves 10th place in the final rankings scoring 0.9004 F1 score for the test set.
Cite
@article{arxiv.2010.05327,
title = {InfoMiner at WNUT-2020 Task 2: Transformer-based Covid-19 Informative Tweet Extraction},
author = {Hansi Hettiarachchi and Tharindu Ranasinghe},
journal= {arXiv preprint arXiv:2010.05327},
year = {2020}
}
Comments
Accepted to the 6th Workshop on Noisy User-generated Text (W-NUT) at EMNLP 2020