Paper accepted @ICWSM 2023 https://ojs.aaai.org/index.php/ICWSM/article/view/22213/21992
We create a publicly available dataset of over 3,100 COVID-19 vaccine-related tweets labelled as one of four stance categories: pro-vaxx, anti-vaxx, vaxx-hesitant, or irrelevant.
We split our dataset into two separate files:
(1) VaccineHesitancy_train_v2.csv (Single + Double annotated)
(2) VaccineHesitancy_test.csv (Double annotated)
Our dataset is publicly available via Zenodo: https://zenodo.org/records/7601328
Our PLM (i.e., covid-vaccine-twitter-bert) is available via HuggingFace: https://huggingface.co/GateNLP/covid-vaccine-twitter-bert
@inproceedings{mu2023vaxxhesitancy,
title={VaxxHesitancy: A Dataset for Studying Hesitancy Towards COVID-19 Vaccination on Twitter},
author={Mu, Yida and Jin, Mali and Grimshaw, Charlie and Scarton, Carolina and Bontcheva, Kalina and Song, Xingyi},
booktitle={Proceedings of the International AAAI Conference on Web and Social Media},
volume={17},
pages={1052--1062},
year={2023}
}