  This paper reviews and summarizes the research results on fact-based fake
news from the perspectives of tasks and problems, algorithm strategies, and
datasets. First, the paper systematically explains the task definition and core
problems of fact-based fake news detection. Second, the paper summarizes the
existing detection methods based on the algorithm principles. Third, the paper
analyzes the classic and newly proposed datasets in the field, and summarizes
the experimental results on each dataset. Finally, the paper summarizes the
advantages and disadvantages of existing methods, proposes several challenges
that methods in this field may face, and looks forward to the next stage of
research. It is hoped that this paper will provide reference for subsequent
work in the field.
