As online false information continues to grow, automated fact-checking has gained an increasing amount of attention in recent years. Researchers in the field of Natural Language Processing (NLP) have contributed to the task by building fact-checking datasets, devising automated fact-checking pipelines and proposing NLP methods to further research in the development of different components. This paper reviews relevant research on automated fact-checking covering both the claim detection and claim validation components.
@article{arxiv.2109.11427,
title = {Automated Fact-Checking: A Survey},
author = {Xia Zeng and Amani S. Abumansour and Arkaitz Zubiaga},
journal= {arXiv preprint arXiv:2109.11427},
year = {2021}
}