Automated Fact-Checking: A Survey
It provides a comprehensive overview for researchers in NLP, but is incremental as it synthesizes existing work without novel contributions.
This survey reviews research on automated fact-checking, addressing the problem of online false information by examining claim detection and validation components, but does not present new results or numbers.
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.