Published December 1, 2022 | Version v1
Dataset Open

Classifying COVID-19 vaccine narratives

Authors/Creators

  • 1. University of Sheffield

Description

We release the augmented Twitter dataset of 355 vaccine-related narratives, created for the following paper. The tweets are labelled as one of four classes: Conspiracy (Cons), Moral, Religious, and Ethical Concerns (MRE), Liberties and Freedom (LF), and Animal Vaccines (AnimalVac).

@article{li2022classifying,
  title={Classifying COVID-19 vaccine narratives},
  author={Li, Yue and Scarton, Carolina and Song, Xingyi and Bontcheva, Kalina},
  journal={arXiv preprint arXiv:2207.08522},
  year={2022}
}

The paper has been accepted by RANLP 2023.

 

 

Notes

This research is also supported by a University of Sheffield QR SPF Grant

Files

Vaccine Narratives Twitter - Data_Augmentation.csv

Files (9.4 kB)

Additional details

Funding

UK Research and Innovation
XAIvsDisinfo: eXplainable AI Methods for Categorisation and Analysis of COVID-19 Vaccine Disinformation and Online Debates EP/W011212/1
European Commission
SoBigData-PlusPlus - SoBigData++: European Integrated Infrastructure for Social Mining and Big Data Analytics 871042